An inter-comparison of PM10 source apportionment using PCA and PMF receptor models in three European sites.

PubMed

Cesari, Daniela; Amato, F; Pandolfi, M; Alastuey, A; Querol, X; Contini, D

2016-08-01

Source apportionment of aerosol is an important approach to investigate aerosol formation and transformation processes as well as to assess appropriate mitigation strategies and to investigate causes of non-compliance with air quality standards (Directive 2008/50/CE). Receptor models (RMs) based on chemical composition of aerosol measured at specific sites are a useful, and widely used, tool to perform source apportionment. However, an analysis of available studies in the scientific literature reveals heterogeneities in the approaches used, in terms of "working variables" such as the number of samples in the dataset and the number of chemical species used as well as in the modeling tools used. In this work, an inter-comparison of PM10 source apportionment results obtained at three European measurement sites is presented, using two receptor models: principal component analysis coupled with multi-linear regression analysis (PCA-MLRA) and positive matrix factorization (PMF). The inter-comparison focuses on source identification, quantification of source contribution to PM10, robustness of the results, and how these are influenced by the number of chemical species available in the datasets. Results show very similar component/factor profiles identified by PCA and PMF, with some discrepancies in the number of factors. The PMF model appears to be more suitable to separate secondary sulfate and secondary nitrate with respect to PCA at least in the datasets analyzed. Further, some difficulties have been observed with PCA in separating industrial and heavy oil combustion contributions. Commonly at all sites, the crustal contributions found with PCA were larger than those found with PMF, and the secondary inorganic aerosol contributions found by PCA were lower than those found by PMF. Site-dependent differences were also observed for traffic and marine contributions. The inter-comparison of source apportionment performed on complete datasets (using the full range of available chemical species) and incomplete datasets (with reduced number of chemical species) allowed to investigate the sensitivity of source apportionment (SA) results to the working variables used in the RMs. Results show that, at both sites, the profiles and the contributions of the different sources calculated with PMF are comparable within the estimated uncertainties indicating a good stability and robustness of PMF results. In contrast, PCA outputs are more sensitive to the chemical species present in the datasets. In PCA, the crustal contributions are higher in the incomplete datasets and the traffic contributions are significantly lower for incomplete datasets.

Selected questions on biomechanical exposures for surveillance of upper-limb work-related musculoskeletal disorders

PubMed Central

Descatha, Alexis; Roquelaure, Yves; Evanoff, Bradley; Niedhammer, Isabelle; Chastang, Jean François; Mariot, Camille; Ha, Catherine; Imbernon, Ellen; Goldberg, Marcel; Leclerc, Annette

2007-01-01

Objective Questionnaires for assessment of biomechanical exposure are frequently used in surveillance programs, though few studies have evaluated which key questions are needed. We sought to reduce the number of variables on a surveillance questionnaire by identifying which variables best summarized biomechanical exposure in a survey of the French working population. Methods We used data from the 2002–2003 French experimental network of Upper-limb work-related musculoskeletal disorders (UWMSD), performed on 2685 subjects in which 37 variables assessing biomechanical exposures were available (divided into four ordinal categories, according to the task frequency or duration). Principal Component Analysis (PCA) with orthogonal rotation was performed on these variables. Variables closely associated with factors issued from PCA were retained, except those highly correlated to another variable (rho>0.70). In order to study the relevance of the final list of variables, correlations between a score based on retained variables (PCA score) and the exposure score suggested by the SALTSA group were calculated. The associations between the PCA score and the prevalence of UWMSD were also studied. In a final step, we added back to the list a few variables not retained by PCA, because of their established recognition as risk factors. Results According to the results of the PCA, seven interpretable factors were identified: posture exposures, repetitiveness, handling of heavy loads, distal biomechanical exposures, computer use, forklift operator specific task, and recovery time. Twenty variables strongly correlated with the factors obtained from PCA were retained. The PCA score was strongly correlated both with the SALTSA score and with UWMSD prevalence (p<0.0001). In the final step, six variables were reintegrated. Conclusion Twenty-six variables out of 37 were efficiently selected according to their ability to summarize major biomechanical constraints in a working population, with an approach combining statistical analyses and existing knowledge. PMID:17476519

An improved optimization algorithm and Bayes factor termination criterion for sequential projection pursuit

DOE Office of Scientific and Technical Information (OSTI.GOV)

Webb-Robertson, Bobbie-Jo M.; Jarman, Kristin H.; Harvey, Scott D.

2005-05-28

A fundamental problem in analysis of highly multivariate spectral or chromatographic data is reduction of dimensionality. Principal components analysis (PCA), concerned with explaining the variance-covariance structure of the data, is a commonly used approach to dimension reduction. Recently an attractive alternative to PCA, sequential projection pursuit (SPP), has been introduced. Designed to elicit clustering tendencies in the data, SPP may be more appropriate when performing clustering or classification analysis. However, the existing genetic algorithm (GA) implementation of SPP has two shortcomings, computation time and inability to determine the number of factors necessary to explain the majority of the structure inmore » the data. We address both these shortcomings. First, we introduce a new SPP algorithm, a random scan sampling algorithm (RSSA), that significantly reduces computation time. We compare the computational burden of the RSS and GA implementation for SPP on a dataset containing Raman spectra of twelve organic compounds. Second, we propose a Bayes factor criterion, BFC, as an effective measure for selecting the number of factors needed to explain the majority of the structure in the data. We compare SPP to PCA on two datasets varying in type, size, and difficulty; in both cases SPP achieves a higher accuracy with a lower number of latent variables.« less

Prediction of Protein Modification Sites of Pyrrolidone Carboxylic Acid Using mRMR Feature Selection and Analysis

PubMed Central

Zheng, Lu-Lu; Niu, Shen; Hao, Pei; Feng, KaiYan; Cai, Yu-Dong; Li, Yixue

2011-01-01

Pyrrolidone carboxylic acid (PCA) is formed during a common post-translational modification (PTM) of extracellular and multi-pass membrane proteins. In this study, we developed a new predictor to predict the modification sites of PCA based on maximum relevance minimum redundancy (mRMR) and incremental feature selection (IFS). We incorporated 727 features that belonged to 7 kinds of protein properties to predict the modification sites, including sequence conservation, residual disorder, amino acid factor, secondary structure and solvent accessibility, gain/loss of amino acid during evolution, propensity of amino acid to be conserved at protein-protein interface and protein surface, and deviation of side chain carbon atom number. Among these 727 features, 244 features were selected by mRMR and IFS as the optimized features for the prediction, with which the prediction model achieved a maximum of MCC of 0.7812. Feature analysis showed that all feature types contributed to the modification process. Further site-specific feature analysis showed that the features derived from PCA's surrounding sites contributed more to the determination of PCA sites than other sites. The detailed feature analysis in this paper might provide important clues for understanding the mechanism of the PCA formation and guide relevant experimental validations. PMID:22174779

Characterizing Variability of Modular Brain Connectivity with Constrained Principal Component Analysis

PubMed Central

Hirayama, Jun-ichiro; Hyvärinen, Aapo; Kiviniemi, Vesa; Kawanabe, Motoaki; Yamashita, Okito

2016-01-01

Characterizing the variability of resting-state functional brain connectivity across subjects and/or over time has recently attracted much attention. Principal component analysis (PCA) serves as a fundamental statistical technique for such analyses. However, performing PCA on high-dimensional connectivity matrices yields complicated “eigenconnectivity” patterns, for which systematic interpretation is a challenging issue. Here, we overcome this issue with a novel constrained PCA method for connectivity matrices by extending the idea of the previously proposed orthogonal connectivity factorization method. Our new method, modular connectivity factorization (MCF), explicitly introduces the modularity of brain networks as a parametric constraint on eigenconnectivity matrices. In particular, MCF analyzes the variability in both intra- and inter-module connectivities, simultaneously finding network modules in a principled, data-driven manner. The parametric constraint provides a compact module-based visualization scheme with which the result can be intuitively interpreted. We develop an optimization algorithm to solve the constrained PCA problem and validate our method in simulation studies and with a resting-state functional connectivity MRI dataset of 986 subjects. The results show that the proposed MCF method successfully reveals the underlying modular eigenconnectivity patterns in more general situations and is a promising alternative to existing methods. PMID:28002474

Source apportionment of PAH in Hamilton Harbour suspended sediments: comparison of two factor analysis methods.

PubMed

Sofowote, Uwayemi M; McCarry, Brian E; Marvin, Christopher H

2008-08-15

A total of 26 suspended sediment samples collected over a 5-year period in Hamilton Harbour, Ontario, Canada and surrounding creeks were analyzed for a suite of polycyclic aromatic hydrocarbons and sulfur heterocycles. Hamilton Harbour sediments contain relatively high levels of polycyclic aromatic compounds and heavy metals due to emissions from industrial and mobile sources. Two receptor modeling methods using factor analyses were compared to determine the profiles and relative contributions of pollution sources to the harbor; these methods are principal component analyses (PCA) with multiple linear regression analysis (MLR) and positive matrix factorization (PMF). Both methods identified four factors and gave excellent correlation coefficients between predicted and measured levels of 25 aromatic compounds; both methods predicted similar contributions from coal tar/coal combustion sources to the harbor (19 and 26%, respectively). One PCA factor was identified as contributions from vehicular emissions (61%); PMF was able to differentiate vehicular emissions into two factors, one attributed to gasoline emissions sources (28%) and the other to diesel emissions sources (24%). Overall, PMF afforded better source identification than PCA with MLR. This work constitutes one of the few examples of the application of PMF to the source apportionment of sediments; the addition of sulfur heterocycles to the analyte list greatly aided in the source identification process.

Exercise and prostate cancer: From basic science to clinical applications.

PubMed

Campos, Christian; Sotomayor, Paula; Jerez, Daniel; González, Javier; Schmidt, Camila B; Schmidt, Katharina; Banzer, Winfried; Godoy, Alejandro S

2018-06-01

Prostate cancer (PCa) is a disease of increasing medical significance worldwide. In developed countries, PCa is the most common non-skin cancer in men, and one of the leading causes of cancer-related deaths. Exercise is one of the environmental factors that have been shown to influence cancer risk. Moreover, systemic reviews and meta-analysis have suggested that total physical activity is related to a decrease in the risk of developing PCa. In addition, epidemiological studies have shown that exercise, after diagnosis, has benefits regarding PCa development, and positive outcome in patients under treatment. The standard treatment for locally advanced or metastatic PCa is Androgen deprivation therapy (ADT). ADT produces diverse side effects, including loss of libido, changes in body composition (increase abdominal fat), and reduced muscle mass, and muscle tone. Analysis of numerous research publications showed that aerobic and/or resistance training improve patient's physical condition, such us, cardiorespiratory fitness, muscle strength, physical function, body composition, and fatigue. Therefore, exercise might counteract several ADT treatment-induced side effects. In addition of the aforementioned benefits, epidemiological, and in vitro studies have shown that exercise might decrease PCa development. Thus, physical activity might attenuate the risk of PCa and supervised exercise intervention might improve deleterious effects of cancer treatment, such as ADT side effects. This review article provides evidence indicating that exercise could complement, and potentiate, the current standard treatments for advanced PCa, probably by creating an unfavorable microenvironment that can negatively affect tumor development, and progression. © 2018 Wiley Periodicals, Inc.

Prostate calculi in cancer and BPH in a cohort of Korean men: presence of calculi did not correlate with cancer risk

PubMed Central

Hwang, Eu-Chang; Choi, Hyang-Sik; Im, Chang-Min; Jung, Seung-Il; Kim, Sun-Ouck; Kang, Taek-Won; Kwon, Dong-Deuk; Park, Kwang-Sung; Ryu, Soo-Bang

2010-01-01

Prostatic calculi are common and are associated with inflammation of the prostate. Recently, it has been suggested that this inflammation may be associated with prostate carcinogenesis. The aim of this study was to investigate the relationship between prostatic calculi and prostate cancer (PCa) in prostate biopsy specimens. We retrospectively analyzed 417 consecutive patients who underwent transrectal ultrasonography (TRUS) and prostate biopsies between January 2005 and January 2008. Based on the biopsy findings, patients were divided into benign prostatic hyperplasia and PCa groups. TRUS was used to detect prostatic calculi and to measure prostate volume. The correlations between PCa risk and age, serum total PSA levels, prostate volume, and prostatic calculi were analyzed. Patient age and PSA, as well as the frequency of prostatic calculi in the biopsy specimens, differed significantly between both the groups (P < 0.05). In the PCa group, the Gleason scores (GSs) were higher in patients with prostatic calculi than in patients without prostatic calculi (P = 0.023). Using multivariate logistic regression analysis, we found that patient age, serum total PSA and prostate volume were risk factors for PCa (P = 0.001), but that the presence of prostatic calculi was not associated with an increased risk of PCa (P = 0.13). In conclusion, although the presence of prostatic calculi was not shown to be a risk factor for PCa, prostatic calculi were more common in patients with PCa and were associated with a higher GS among these men. PMID:20037598

Prognostic value of transformer 2β expression in prostate cancer.

PubMed

Diao, Yan; Wu, Dong; Dai, Zhijun; Kang, Huafeng; Wang, Ziming; Wang, Xijing

2015-01-01

Deregulation of transformer 2β (Tra2β) has been implicated in several cancers. However, the role of Tra2β expression in prostate cancer (PCa) is unclear. Therefore, this study was to investigate the expression of Tra2β in PCa and evaluated its association with clinicopathological variables and prognosis. Thirty paired fresh PCa samples were analyzed for Tra2β expression by Western blot analysis. Immunohistochemistry (IHC) assay was performed in 160 PCa samples after radical prostatectomy and adjacent non-cancerous tissues. Tra2β protein expression was divided into high expression group and low expression group by IHC. We also investigated the association of Tra2β expression with clinical and pathologic parameters. Kaplan-Meier plots and Cox proportional hazards regression model were used to analyze the association between Tra2β protein expression and prognosis of PCa patients. Our results showed that Tra2β was significantly upregulated in PCa tissues by western blot and IHC. Our data indicated that high expression of Tra2β was significantly associated with lymph node metastasis (P=0.002), clinical stage (P=0.015), preoperative prostate-specific antigen (P=0.003), Gleason score (P=0.001), and biochemical recurrence (P=0.021). High Tra2β expression was a significant predictor of poor biochemical recurrence free survival and overall survival both in univariate and multivariate analysis. We show that Tra2β was significantly upregulated in PCa patients after radical prostatectomy, and multivariate analysis confirmed Tra2β as an independent prognostic factor.

Sparse PCA corrects for cell type heterogeneity in epigenome-wide association studies.

PubMed

Rahmani, Elior; Zaitlen, Noah; Baran, Yael; Eng, Celeste; Hu, Donglei; Galanter, Joshua; Oh, Sam; Burchard, Esteban G; Eskin, Eleazar; Zou, James; Halperin, Eran

2016-05-01

In epigenome-wide association studies (EWAS), different methylation profiles of distinct cell types may lead to false discoveries. We introduce ReFACTor, a method based on principal component analysis (PCA) and designed for the correction of cell type heterogeneity in EWAS. ReFACTor does not require knowledge of cell counts, and it provides improved estimates of cell type composition, resulting in improved power and control for false positives in EWAS. Corresponding software is available at http://www.cs.tau.ac.il/~heran/cozygene/software/refactor.html.

Exploring factors affecting owners' trust of contractors in construction projects: a case of China.

PubMed

Tai, Shuangliang; Sun, Chengshuang; Zhang, Shoujian

2016-01-01

It has been found that a low level of trust among members of a construction project team leads to poor performance in China. Many researchers have described the challenges, consequently advocating partnering as an attractive approach for more valuable cooperation. Because substantial investments have been poured into construction projects since the year 2000, trust research will improve the performance of construction projects and will be meaningful to the Chinese construction industry. The purpose of this paper is to investigate the attributes affecting owners' trust of contractors, to understand the potential properties of these factors, and to rank the factors in order of importance. Twenty-four attributes are identified from a literature review. Supported by qualitative reviews, a questionnaire is conducted to obtain relevant data, and 168 valid responses are obtained for data analysis. Principal component analysis (PCA) is employed to find the factor structure of the identified trust attributes. By the method of PCA, the attributes are extracted into eight factors, including interaction history, information sharing and communication, contract and institution, relation-specific investment, reputation, integrity, competence, and opportunistic behaviour. The value and originality of this paper are embodied in using PCA to understand the various attribute groupings and to illuminate trust impact factors in the Chinese context. When they understand the critical factors affecting trust better, owners and contractors can devise more appropriate strategies to improve performance.

EMPCA and Cluster Analysis of Quasar Spectra: Construction and Application to Simulated Spectra

NASA Astrophysics Data System (ADS)

Marrs, Adam; Leighly, Karen; Wagner, Cassidy; Macinnis, Francis

2017-01-01

Quasars have complex spectra with emission lines influenced by many factors. Therefore, to fully describe the spectrum requires specification of a large number of parameters, such as line equivalent width, blueshift, and ratios. Principal Component Analysis (PCA) aims to construct eigenvectors-or principal components-from the data with the goal of finding a few key parameters that can be used to predict the rest of the spectrum fairly well. Analysis of simulated quasar spectra was used to verify and justify our modified application of PCA.We used a variant of PCA called Weighted Expectation Maximization PCA (EMPCA; Bailey 2012) along with k-means cluster analysis to analyze simulated quasar spectra. Our approach combines both analytical methods to address two known problems with classical PCA. EMPCA uses weights to account for uncertainty and missing points in the spectra. K-means groups similar spectra together to address the nonlinearity of quasar spectra, specifically variance in blueshifts and widths of the emission lines.In producing and analyzing simulations, we first tested the effects of varying equivalent widths and blueshifts on the derived principal components, and explored the differences between standard PCA and EMPCA. We also tested the effects of varying signal-to-noise ratio. Next we used the results of fits to composite quasar spectra (see accompanying poster by Wagner et al.) to construct a set of realistic simulated spectra, and subjected those spectra to the EMPCA /k-means analysis. We concluded that our approach was validated when we found that the mean spectra from our k-means clusters derived from PCA projection coefficients reproduced the trends observed in the composite spectra.Furthermore, our method needed only two eigenvectors to identify both sets of correlations used to construct the simulations, as well as indicating the linear and nonlinear segments. Comparing this to regular PCA, which can require a dozen or more components, or to direct spectral analysis that may need measurement of 20 fit parameters, shows why the dual application of these two techniques is such a powerful tool.

Prebiotic Low Sugar Chocolate Dairy Desserts: Physical and Optical Characteristics and Performance of PARAFAC and PCA Preference Map.

PubMed

Morais, E C; Esmerino, E A; Monteiro, R A; Pinheiro, C M; Nunes, C A; Cruz, A G; Bolini, Helena M A

2016-01-01

The addition of prebiotic and sweeteners in chocolate dairy desserts opens up new opportunities to develop dairy desserts that besides having a lower calorie intake still has functional properties. In this study, prebiotic low sugar dairy desserts were evaluated by 120 consumers using a 9-point hedonic scale, in relation to the attributes of appearance, aroma, flavor, texture, and overall liking. Internal preference map using parallel factor analysis (PARAFAC) and principal component analysis (PCA) was performed using the consumer data. In addition, physical (texture profile) and optical (instrumental color) analyses were also performed. Prebiotic dairy desserts containing sucrose and sucralose were equally liked by the consumers. These samples were characterized by firmness and gumminess, which can be considered drivers of liking by the consumers. Optimization of the prebiotic low sugar dessert formulation should take in account the choice of ingredients that contribute in a positive manner for these parameters. PARAFAC allowed the extraction of more relevant information in relation to PCA, demonstrating that consumer acceptance analysis can be evaluated by simultaneously considering several attributes. Multiple factor analysis reported Rv value of 0.964, suggesting excellent concordance for both methods. © 2015 Institute of Food Technologists®

Infiltration of tumour-associated macrophages in prostate biopsy specimens is predictive of disease progression after hormonal therapy for prostate cancer.

PubMed

Nonomura, Norio; Takayama, Hitoshi; Nakayama, Masashi; Nakai, Yasutomo; Kawashima, Atsunari; Mukai, Masatoshi; Nagahara, Akira; Aozasa, Katsuyuki; Tsujimura, Akira

2011-06-01

• To evaluate tumour-associated macrophage (TAM) infiltration in prostate biopsy specimens as a possible prognostic factor for prostate cancer (PCa) after hormonal therapy. • Immunostaining of TAMs in prostate biopsy specimens was performed using a monoclonal antibody CD68 for 71 patients having PCa treated with hormonal therapy. • Six microscopic (×400) fields around the cancer foci were selected for TAM counting. • The median value of serum prostate-specific antigen (PSA) was 50.1 ng/mL, and the median TAM count was 22. • Recurrence-free survival was significantly better in patients with fewer TAMs (<22) than in those with higher numbers of TAMs (≥22) (P < 0.001). • TAM count was higher in those with higher serum PSA (PSA), higher Gleason score, clinical T stage or those with PSA failure. Cox multivariate analysis showed that TAM count is one of the prognostic factors for PCa treated by hormonal therapy (P < 0.0001). • TAM infiltration in prostate needle biopsy specimens is a useful predictive factor for PSA failure or progression of PCa after hormonal therapy. © 2010 THE AUTHORS. BJU INTERNATIONAL © 2010 BJU INTERNATIONAL.

Identifying natural and anthropogenic sources of metals in urban and rural soils using GIS-based data, PCA, and spatial interpolation

PubMed Central

Davis, Harley T.; Aelion, C. Marjorie; McDermott, Suzanne; Lawson, Andrew B.

2009-01-01

Determining sources of neurotoxic metals in rural and urban soils is important for mitigating human exposure. Surface soil from four areas with significant clusters of mental retardation and developmental delay (MR/DD) in children, and one control site were analyzed for nine metals and characterized by soil type, climate, ecological region, land use and industrial facilities using readily-available GIS-based data. Kriging, principal component analysis (PCA) and cluster analysis (CA) were used to identify commonalities of metal distribution. Three MR/DD areas (one rural and two urban) had similar soil types and significantly higher soil metal concentrations. PCA and CA results suggested that Ba, Be and Mn were consistently from natural sources; Pb and Hg from anthropogenic sources; and As, Cr, Cu, and Ni from both sources. Arsenic had low commonality estimates, was highly associated with a third PCA factor, and had a complex distribution, complicating mitigation strategies to minimize concentrations and exposures. PMID:19361902

Short-term PV/T module temperature prediction based on PCA-RBF neural network

NASA Astrophysics Data System (ADS)

Li, Jiyong; Zhao, Zhendong; Li, Yisheng; Xiao, Jing; Tang, Yunfeng

2018-02-01

Aiming at the non-linearity and large inertia of temperature control in PV/T system, short-term temperature prediction of PV/T module is proposed, to make the PV/T system controller run forward according to the short-term forecasting situation to optimize control effect. Based on the analysis of the correlation between PV/T module temperature and meteorological factors, and the temperature of adjacent time series, the principal component analysis (PCA) method is used to pre-process the original input sample data. Combined with the RBF neural network theory, the simulation results show that the PCA method makes the prediction accuracy of the network model higher and the generalization performance stronger than that of the RBF neural network without the main component extraction.

Personal and couple level risk factors: Maternal and paternal parent-child aggression risk.

PubMed

Tucker, Meagan C; Rodriguez, Christina M; Baker, Levi R

2017-07-01

Previous literature examining parent-child aggression (PCA) risk has relied heavily upon mothers, limiting our understanding of paternal risk factors. Moreover, the extent to which factors in the couple relationship work in tandem with personal vulnerabilities to impact PCA risk is unclear. The current study examined whether personal stress and distress predicted PCA risk (child abuse potential, over-reactive discipline style, harsh discipline practices) for fathers as well as mothers and whether couple functioning mediated versus moderated the relation between personal stress and PCA risk in a sample of 81 couples. Additionally, the potential for risk factors in one partner to cross over and affect their partner's PCA risk was considered. Findings indicated higher personal stress predicted elevated maternal and paternal PCA risk. Better couple functioning did not moderate this relationship but partially mediated stress and PCA risk for both mothers and fathers. In addition, maternal stress evidenced a cross-over effect, wherein mothers' personal stress linked to fathers' couple functioning. Findings support the role of stress and couple functioning in maternal and paternal PCA risk, including potential cross-over effects that warrant further inquiry. Copyright © 2017 Elsevier Ltd. All rights reserved.

IMPROVED SEARCH OF PRINCIPAL COMPONENT ANALYSIS DATABASES FOR SPECTRO-POLARIMETRIC INVERSION

DOE Office of Scientific and Technical Information (OSTI.GOV)

Casini, R.; Lites, B. W.; Ramos, A. Asensio

2013-08-20

We describe a simple technique for the acceleration of spectro-polarimetric inversions based on principal component analysis (PCA) of Stokes profiles. This technique involves the indexing of the database models based on the sign of the projections (PCA coefficients) of the first few relevant orders of principal components of the four Stokes parameters. In this way, each model in the database can be attributed a distinctive binary number of 2{sup 4n} bits, where n is the number of PCA orders used for the indexing. Each of these binary numbers (indices) identifies a group of ''compatible'' models for the inversion of amore » given set of observed Stokes profiles sharing the same index. The complete set of the binary numbers so constructed evidently determines a partition of the database. The search of the database for the PCA inversion of spectro-polarimetric data can profit greatly from this indexing. In practical cases it becomes possible to approach the ideal acceleration factor of 2{sup 4n} as compared to the systematic search of a non-indexed database for a traditional PCA inversion. This indexing method relies on the existence of a physical meaning in the sign of the PCA coefficients of a model. For this reason, the presence of model ambiguities and of spectro-polarimetric noise in the observations limits in practice the number n of relevant PCA orders that can be used for the indexing.« less

Physical activity in relation to risk of prostate cancer: a systematic review and meta-analysis.

PubMed

Benke, I N; Leitzmann, M F; Behrens, G; Schmid, D

2018-05-01

Prostate cancer (PCa) is one of the most common cancers among men, yet little is known about its modifiable risk and protective factors. This study aims to quantitatively summarize observational studies relating physical activity (PA) to PCa incidence and mortality. Published articles pertaining to PA and PCa incidence and mortality were retrieved in July 2017 using the Medline and EMBASE databases. The literature review yielded 48 cohort studies and 24 case-control studies with a total of 151 748 PCa cases. The mean age of the study participants at baseline was 61 years. In random-effects models, comparing the highest versus the lowest level of overall PA showed a summary relative risk (RR) estimate for total PCa incidence close to the null [RR = 0.99, 95% confidence interval (CI) = 0.94-1.04]. The corresponding RRs for advanced and non-advanced PCa were 0.92 (95% CI = 0.80-1.06) and 0.95 (95% CI = 0.85-1.07), respectively. We noted a statistically significant inverse association between long-term occupational activity and total PCa (RR = 0.83, 95% CI = 0.71-0.98, n studies = 13), although that finding became statistically non-significant when individual studies were removed from the analysis. When evaluated by cancer subtype, an inverse association with long-term occupational activity was noted for non-advanced/non-aggressive PCa (RR = 0.51, 95% CI = 0.37-0.71, n studies = 2) and regular recreational activity was inversely related to advanced/aggressive PCa (RR = 0.75, 95% CI = 0.60-0.95, n studies = 2), although these observations are based on a low number of studies. Moreover, PA after diagnosis was related to reduced risk of PCa mortality among survivors of PCa (summary RR based on four studies = 0.69, 95% CI = 0.55-0.85). Whether PA protects against PCa remains elusive. Further investigation taking into account the complex clinical and pathologic nature of PCa is needed to clarify the PA and PCa incidence relation. Moreover, future studies are needed to confirm whether PA after diagnosis reduces risk of PCa mortality.

Identification and apportionment of hazardous elements in the sediments in the Yangtze River estuary.

PubMed

Wang, Jiawei; Liu, Ruimin; Wang, Haotian; Yu, Wenwen; Xu, Fei; Shen, Zhenyao

2015-12-01

In this study, positive matrix factorization (PMF) and principal components analysis (PCA) were combined to identify and apportion pollution-based sources of hazardous elements in the surface sediments in the Yangtze River estuary (YRE). Source identification analysis indicated that PC1, including Al, Fe, Mn, Cr, Ni, As, Cu, and Zn, can be defined as a sewage component; PC2, including Pb and Sb, can be considered as an atmospheric deposition component; and PC3, containing Cd and Hg, can be considered as an agricultural nonpoint component. To better identify the sources and quantitatively apportion the concentrations to their sources, eight sources were identified with PMF: agricultural/industrial sewage mixed (18.6 %), mining wastewater (15.9 %), agricultural fertilizer (14.5 %), atmospheric deposition (12.8 %), agricultural nonpoint (10.6 %), industrial wastewater (9.8 %), marine activity (9.0 %), and nickel plating industry (8.8 %). Overall, the hazardous element content seems to be more connected to anthropogenic activity instead of natural sources. The PCA results laid the foundation for the PMF analysis by providing a general classification of sources. PMF resolves more factors with a higher explained variance than PCA; PMF provided both the internal analysis and the quantitative analysis. The combination of the two methods can provide more reasonable and reliable results.

Optimization of sol-gel technique for coating of metallic substrates by hydroxyapatite using the Taguchi method

NASA Astrophysics Data System (ADS)

Pourbaghi-Masouleh, M.; Asgharzadeh, H.

2013-08-01

In this study, the Taguchi method of design of experiment (DOE) was used to optimize the hydroxyapatite (HA) coatings on various metallic substrates deposited by sol-gel dip-coating technique. The experimental design consisted of five factors including substrate material (A), surface preparation of substrate (B), dipping/withdrawal speed (C), number of layers (D), and calcination temperature (E) with three levels of each factor. An orthogonal array of L18 type with mixed levels of the control factors was utilized. The image processing of the micrographs of the coatings was conducted to determine the percentage of coated area ( PCA). Chemical and phase composition of HA coatings were studied by XRD, FT-IR, SEM, and EDS techniques. The analysis of variance (ANOVA) indicated that the PCA of HA coatings was significantly affected by the calcination temperature. The optimum conditions from signal-to-noise ( S/N) ratio analysis were A: pure Ti, B: polishing and etching for 24 h, C: 50 cm min-1, D: 1, and E: 300 °C. In the confirmation experiment using the optimum conditions, the HA coating with high PCA of 98.5 % was obtained.

Systems genetic analysis of multivariate response to iron deficiency in mice

PubMed Central

Yin, Lina; Unger, Erica L.; Jellen, Leslie C.; Earley, Christopher J.; Allen, Richard P.; Tomaszewicz, Ann; Fleet, James C.

2012-01-01

The aim of this study was to identify genes that influence iron regulation under varying dietary iron availability. Male and female mice from 20+ BXD recombinant inbred strains were fed iron-poor or iron-adequate diets from weaning until 4 mo of age. At death, the spleen, liver, and blood were harvested for the measurement of hemoglobin, hematocrit, total iron binding capacity, transferrin saturation, and liver, spleen and plasma iron concentration. For each measure and diet, we found large, strain-related variability. A principal-components analysis (PCA) was performed on the strain means for the seven parameters under each dietary condition for each sex, followed by quantitative trait loci (QTL) analysis on the factors. Compared with the iron-adequate diet, iron deficiency altered the factor structure of the principal components. QTL analysis, combined with PosMed (a candidate gene searching system) published gene expression data and literature citations, identified seven candidate genes, Ptprd, Mdm1, Picalm, lip1, Tcerg1, Skp2, and Frzb based on PCA factor, diet, and sex. Expression of each of these is cis-regulated, significantly correlated with the corresponding PCA factor, and previously reported to regulate iron, directly or indirectly. We propose that polymorphisms in multiple genes underlie individual differences in iron regulation, especially in response to dietary iron challenge. This research shows that iron management is a highly complex trait, influenced by multiple genes. Systems genetics analysis of iron homeostasis holds promise for developing new methods for prevention and treatment of iron deficiency anemia and related diseases. PMID:22461179

Recruitment Methods and Show Rates to a Prostate Cancer Early Detection Program for High-Risk Men: A Comprehensive Analysis

PubMed Central

Giri, Veda N.; Coups, Elliot J.; Ruth, Karen; Goplerud, Julia; Raysor, Susan; Kim, Taylor Y.; Bagden, Loretta; Mastalski, Kathleen; Zakrzewski, Debra; Leimkuhler, Suzanne; Watkins-Bruner, Deborah

2009-01-01

Purpose Men with a family history (FH) of prostate cancer (PCA) and African American (AA) men are at higher risk for PCA. Recruitment and retention of these high-risk men into early detection programs has been challenging. We report a comprehensive analysis on recruitment methods, show rates, and participant factors from the Prostate Cancer Risk Assessment Program (PRAP), which is a prospective, longitudinal PCA screening study. Materials and Methods Men 35–69 years are eligible if they have a FH of PCA, are AA, or have a BRCA1/2 mutation. Recruitment methods were analyzed with respect to participant demographics and show to the first PRAP appointment using standard statistical methods Results Out of 707 men recruited, 64.9% showed to the initial PRAP appointment. More individuals were recruited via radio than from referral or other methods (χ2 = 298.13, p < .0001). Men recruited via radio were more likely to be AA (p<0.001), less educated (p=0.003), not married or partnered (p=0.007), and have no FH of PCA (p<0.001). Men recruited via referrals had higher incomes (p=0.007). Men recruited via referral were more likely to attend their initial PRAP visit than those recruited by radio or other methods (χ2 = 27.08, p < .0001). Conclusions This comprehensive analysis finds that radio leads to higher recruitment of AA men with lower socioeconomic status. However, these are the high-risk men that have lower show rates for PCA screening. Targeted motivational measures need to be studied to improve show rates for PCA risk assessment for these high-risk men. PMID:19758657

A GRAPHICAL DIAGNOSTIC METHOD FOR ASSESSING THE ROTATION IN FACTOR ANALYTICAL MODELS OF ATMOSPHERIC POLLUTION. (R831078)

EPA Science Inventory

Factor analytic tools such as principal component analysis (PCA) and positive matrix factorization (PMF), suffer from rotational ambiguity in the results: different solutions (factors) provide equally good fits to the measured data. The PMF model imposes non-negativity of both...

Prostate Cancer Radiation Therapy and Risk of Thromboembolic Events

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bosco, Cecilia, E-mail: Cecilia.t.bosco@kcl.ac.uk; Garmo, Hans; Regional Cancer Centre, Uppsala, Akademiska Sjukhuset, Uppsala

Purpose: To investigate the risk of thromboembolic disease (TED) after radiation therapy (RT) with curative intent for prostate cancer (PCa). Patients and Methods: We identified all men who received RT as curative treatment (n=9410) and grouped according to external beam RT (EBRT) or brachytherapy (BT). By comparing with an age- and county-matched comparison cohort of PCa-free men (n=46,826), we investigated risk of TED after RT using Cox proportional hazard regression models. The model was adjusted for tumor characteristics, demographics, comorbidities, PCa treatments, and known risk factors of TED, such as recent surgery and disease progression. Results: Between 2006 and 2013, 6232more » men with PCa received EBRT, and 3178 underwent BT. A statistically significant association was found between EBRT and BT and risk of pulmonary embolism in the crude analysis. However, upon adjusting for known TED risk factors these associations disappeared. No significant associations were found between BT or EBRT and deep venous thrombosis. Conclusion: Curative RT for prostate cancer using contemporary methodologies was not associated with an increased risk of TED.« less

The development of summary components for the Disablement in the Physically Active scale in collegiate athletes.

PubMed

Houston, Megan N; Hoch, Johanna M; Van Lunen, Bonnie L; Hoch, Matthew C

2015-11-01

The Disablement in the Physically Active scale (DPA) is a generic patient-reported outcome designed to evaluate constructs of disability in physically active populations. The purpose of this study was to analyze the DPA scale structure for summary components. Four hundred and fifty-six collegiate athletes completed a demographic form and the DPA. A principal component analysis (PCA) was conducted with oblique rotation. Factors with eigenvalues >1 that explained >5 % of the variance were retained. The PCA revealed a two-factor structure consistent with paradigms used to develop the original DPA. Items 1-12 loaded on Factors 1 and Items 13-16 loaded on Factor 2. Items 1-12 pertain to impairment, activity limitations, and participation restrictions. Items 13-16 address psychosocial and emotional well-being. Consideration of item content suggested Factor 1 concerned physical function, while Factor 2 concerned mental well-being. Thus, items clustered around Factor 1 and 2 were identified as physical (DPA-PSC) and mental (DPA-MSC) summary components, respectively. Together, the factors accounted for 65.1 % of the variance. The PCA revealed a two-factor structure for the DPA that resulted in DPA-PSC and DPA-MSC. Analyzing the DPA as separate constructs may provide distinct information that could help to prescribe treatment and rehabilitation strategies.

[Near infrared reflectance spectroscopy (NIRS): a novel approach to reconstructing historical changes of primary productivity in Antarctic lake].

PubMed

Chen, Qian-Qian; Liu, Xiao-Dong; Liu, Wen-Qi; Jiang, Shan

2011-10-01

Compared with traditional chemical analysis methods, reflectance spectroscopy has the advantages of speed, minimal or no sample preparation, non-destruction, and low cost. In order to explore the potential application of spectroscopy technology in the paleolimnological study on Antarctic lakes, we took a lake sediment core in Mochou Lake at Zhongshan Station of Antarctic, and analyzed the near infrared reflectance spectroscopy (NIRS) data in the sedimentary samples. The results showed that the factor loadings of principal component analysis (PCA) displayed very similar depth-profile change pattern with the S2 index, a reliable proxy for the change in historical lake primary productivity. The correlation analysis showed that the values of PCA factor loading and S2 were correlated significantly, suggesting that it is feasible to infer paleoproductivity changes recorded in Antarctic lakes using NIRS technology. Compared to the traditional method of the trough area between 650 and 700 nm, the authors found that the PCA statistical approach was more accurate for reconstructing the change in historical lake primary productivity. The results reported here demonstrate that reflectance spectroscopy can provide a rapid method for the reconstruction of lake palaeoenviro nmental change in the remote Antarctic regions.

Hypoxia on the Expression of Hepatoma Upregulated Protein in Prostate Cancer Cells

PubMed Central

Espinoza, Ingrid; Sakiyama, Marcelo J.; Ma, Tangeng; Fair, Logan; Zhou, Xinchun; Hassan, Mohamed; Zabaleta, Jovanny; Gomez, Christian R.

2016-01-01

Hepatoma upregulated protein (HURP) is a multifunctional protein with clinical promise. This protein has been demonstrated to be a predictive marker for the outcome in high-risk prostate cancer (PCa) patients, besides being a resistance factor in PCa. Although changes in oxygen tension (pO2) are associated with PCa aggressiveness, the role of hypoxia in the regulation of tumor progression genes such as HURP has not yet been described. We hypothesized that pO2 alteration is involved in the regulation of HURP expression in PCa cells. In the present study, PCa cells were incubated at 2% O2 (hypoxia) and 20% O2 (normoxia) conditions. Hypoxia reduced cell growth rate of PCa cells, when compared to the growth rate of cells cultured under normoxia (p < 0.05). The decrease in cell viability was accompanied by fivefold (p < 0.05) elevated rate of vascular endothelial growth factor (VEGF) release. The expression of VEGF and the hypoxia-inducible metabolic enzyme carbonic anhydrase 9 were elevated maximally nearly 61-fold and 200-fold, respectively (p < 0.05). Noted in two cell lines (LNCaP and C4-2B) and independent of the oxygen levels, HURP expression assessed at both mRNA and protein levels was reduced. However, the decrease was more pronounced in cells cultured under hypoxia (p < 0.05). Interestingly, the analysis of patients’ specimens by Western blot revealed a marked increase of HURP protein (fivefold), when compared to control (cystoprostatectomy) tissue (p < 0.05). Immunohistochemistry analysis showed an increase in the immunostaining intensity of HURP and the hypoxia-sensitive molecules, hypoxia-inducible factor 1-alpha (HIF-1α), VEGF, and heat-shock protein 60 (HSP60) in association with tumor grade. The data also suggested a redistribution of subcellular localization for HURP and HIF-1α from the nucleus to the cytoplasmic compartment in relation to increasing tumor grade. Analysis of HURP Promoter for HIF-1-binding sites revealed presence of four putative HIF binding sites on the promoter of DLGAP5/HURP gene in the non-translated region upstream from the start codon, suggesting association between HIF-1α and the regulation of HURP protein. Taken together, our findings suggest a modulatory role of hypoxia on the expression of HURP. Additionally our results provide basis for utilization of tumor-associated molecules as predictors of aggressive PCa. PMID:27379206

Association between age-related reductions in testosterone and risk of prostate cancer-An analysis of patients' data with prostatic diseases.

PubMed

Wang, Kai; Chen, Xinguang; Bird, Victoria Y; Gerke, Travis A; Manini, Todd M; Prosperi, Mattia

2017-11-01

The relationship between serum total testosterone and prostate cancer (PCa) risk is controversial. The hypothesis that faster age-related reduction in testosterone is linked with increased PCa risk remains untested. We conducted our study at a tertiary-level hospital in southeast of the USA, and derived data from the Medical Registry Database of individuals that were diagnosed of any prostate-related disease from 2001 to 2015. Cases were those diagnosed of PCa and had one or more measurements of testosterone prior to PCa diagnosis. Controls were those without PCa and had one or more testosterone measurements. Multivariable logistic regression models for PCa risk of absolute levels (one-time measure and 5-year average) and annual change in testosterone were respectively constructed. Among a total of 1,559 patients, 217 were PCa cases, and neither one-time measure nor 5-year average of testosterone was found to be significantly associated with PCa risk. Among the 379 patients with two or more testosterone measurements, 27 were PCa cases. For every 10 ng/dL increment in annual reduction of testosterone, the risk of PCa would increase by 14% [adjusted odds ratio, 1.14; 95% confidence interval (CI), 1.03-1.25]. Compared to patients with a relatively stable testosterone, patients with an annual testosterone reduction of more than 30 ng/dL had 5.03 [95% CI: 1.53, 16.55] fold increase in PCa risk. This implies a faster age-related reduction in, but not absolute level of serum total testosterone as a risk factor for PCa. Further longitudinal studies are needed to confirm this finding. © 2017 UICC.

Differential principal component analysis of ChIP-seq.

PubMed

Ji, Hongkai; Li, Xia; Wang, Qian-fei; Ning, Yang

2013-04-23

We propose differential principal component analysis (dPCA) for analyzing multiple ChIP-sequencing datasets to identify differential protein-DNA interactions between two biological conditions. dPCA integrates unsupervised pattern discovery, dimension reduction, and statistical inference into a single framework. It uses a small number of principal components to summarize concisely the major multiprotein synergistic differential patterns between the two conditions. For each pattern, it detects and prioritizes differential genomic loci by comparing the between-condition differences with the within-condition variation among replicate samples. dPCA provides a unique tool for efficiently analyzing large amounts of ChIP-sequencing data to study dynamic changes of gene regulation across different biological conditions. We demonstrate this approach through analyses of differential chromatin patterns at transcription factor binding sites and promoters as well as allele-specific protein-DNA interactions.

Multimethod Prediction of Physical Parent-Child Aggression Risk in Expectant Mothers and Fathers with Social Information Processing Theory

PubMed Central

Rodriguez, Christina M.; Smith, Tamika L.; Silvia, Paul J.

2015-01-01

The Social Information Processing (SIP) model postulates that parents undergo a series of stages in implementing physical discipline that can escalate into physical child abuse. The current study utilized a multimethod approach to investigate whether SIP factors can predict risk of parent-child aggression (PCA) in a diverse sample of expectant mothers and fathers. SIP factors of PCA attitudes, negative child attributions, reactivity, and empathy were considered as potential predictors of PCA risk; additionally, analyses considered whether personal history of PCA predicted participants’ own PCA risk through its influence on their attitudes and attributions. Findings indicate that, for both mothers and fathers, history influenced attitudes but not attributions in predicting PCA risk, and attitudes and attributions predicted PCA risk; empathy and reactivity predicted negative child attributions for expectant mothers, but only reactivity significantly predicted attributions for expectant fathers. Path models for expectant mothers and fathers were remarkably similar. Overall, the findings provide support for major aspects of the SIP model. Continued work is needed in studying the progression of these factors across time for both mothers and fathers as well as the inclusion of other relevant ecological factors to the SIP model. PMID:26631420

Effect of transforming growth factor beta (TGF-β) receptor I kinase inhibitor on prostate cancer bone growth.

PubMed

Wan, Xinhai; Li, Zhi-Gang; Yingling, Jonathan M; Yang, Jun; Starbuck, Michael W; Ravoori, Murali K; Kundra, Vikas; Vazquez, Elba; Navone, Nora M

2012-03-01

Transforming growth factor beta 1 (TGF-β1) has been implicated in the pathogenesis of prostate cancer (PCa) bone metastasis. In this study, we tested the antitumor efficacy of a selective TGF-β receptor I kinase inhibitor, LY2109761, in preclinical models. The effect of LY2109761 on the growth of MDA PCa 2b and PC-3 human PCa cells and primary mouse osteoblasts (PMOs) was assessed in vitro by measuring radiolabeled thymidine incorporation into DNA. In vivo, the right femurs of male SCID mice were injected with PCa cells. We monitored the tumor burden in control- and LY2109761-treated mice with MRI analysis and the PCa-induced bone response with X-ray and micro-CT analyses. Histologic changes in bone were studied by performing bone histomorphometric evaluations. PCa cells and PMOs expressed TGF-β receptor I. TGF-β1 induced pathway activation (as assessed by induced expression of p-Smad2) and inhibited cell growth in PC-3 cells and PMOs but not in MDA PCa 2b cells. LY2109761 had no effect on PCa cells but induced PMO proliferation in vitro. As expected, LY2109761 reversed the TGF-β1-induced pathway activation and growth inhibition in PC-3 cells and PMOs. In vivo, LY2109761 treatment for 6weeks resulted in increased volume in normal bone and increased osteoblast and osteoclast parameters. In addition, LY2109761 treatment significantly inhibited the growth of MDA PCa 2b and PC-3 in the bone of SCID mice (p<0.05); moreover, it resulted in significantly less bone loss and change in osteoclast-associated parameters in the PC-3 tumor-bearing bones than in the untreated mice. In summary, we report for the first time that targeting TGF-β receptors with LY2109761 can control PCa bone growth while increasing the mass of normal bone. This increased bone mass in nontumorous bone may be a desirable side effect of LY2109761 treatment for men with osteopenia or osteoporosis secondary to androgen-ablation therapy, reinforcing the benefit of effectively controlling PCa growth in bone. Thus, targeting TGF-β receptor I is a valuable intervention in men with advanced PCa. Copyright © 2011 Elsevier Inc. All rights reserved.

Effect of transforming growth factor beta (TGF-β) receptor I kinase inhibitor on prostate cancer bone growth

PubMed Central

Wan, Xinhai; Li, Zhi-Gang; Yingling, Jonathan M.; Yang, Jun; Starbuck, Michael W.; Ravoori, Murali K.; Kundra, Vikas; Vazquez, Elba; Navone, Nora M.

2012-01-01

Transforming growth factor beta 1 (TGF-β1) has been implicated in the pathogenesis of prostate cancer (PCa) bone metastasis. In this study, we tested the antitumor efficacy of a selective TGF-β receptor I kinase inhibitor, LY2109761, in preclinical models. The effect of LY2109761 on the growth of MDA PCa 2b and PC-3 human PCa cells and primary mouse osteoblasts (PMOs) was assessed in vitro by measuring radiolabeled thymidine incorporation into DNA. In vivo, the right femurs of male SCID mice were injected with PCa cells. We monitored the tumor burden in control- and LY2109761-treated mice with MRI analysis and the PCa-induced bone response with x-ray and micro-CT analyses. Histologic changes in bone were studied by performing bone histomorphometric evaluations. PCa cells and PMOs expressed TGF-β receptor I. TGF-β1 induced pathway activation (as assessed by induced expression of p-Smad2) and inhibited cell growth in PC-3 cells and PMOs but not in MDA PCa 2b cells. LY2109761 had no effect on PCa cells but induced PMO proliferation in vitro. As expected, LY2109761 reversed the TGF-β1–induced pathway activation and growth inhibition in PC-3 cells and PMOs. In vivo, LY2109761 treatment for 6 weeks resulted in increased volume in normal bone and increased osteoblast and osteoclast parameters. In addition, LY2109761 treatment significantly inhibited the growth of MDA PCa 2b and PC-3 in the bone of SCID mice (p < 0.05); moreover, it resulted in significantly less bone loss and change in osteoclast-associated parameters in the PC-3 tumor–bearing bones than in the untreated mice. In summary, we report for the first time that targeting TGF-β receptors with LY2109761 can control PCa bone growth while increasing the mass of normal bone. This increased bone mass in nontumorous bone may be a desirable side effect of LY2109761 treatment for men with osteopenia or osteoporosis secondary to androgen-ablation therapy, reinforcing the benefit of effectively controlling PCa growth in bone. Thus, targeting TGF-β receptor I is a valuable intervention in men with advanced PCa. PMID:22173053

A case-control study of lower urinary-tract infections, associated antibiotics and the risk of developing prostate cancer using PCBaSe 3.0.

PubMed

Russell, Beth; Garmo, Hans; Beckmann, Kerri; Stattin, Pär; Adolfsson, Jan; Van Hemelrijck, Mieke

2018-01-01

To investigate the association between lower urinary-tract infections, their associated antibiotics and the subsequent risk of developing PCa. Using data from the Swedish PCBaSe 3.0, we performed a matched case-control study (8762 cases and 43806 controls). Conditional logistic regression analysis was used to assess the association between lower urinary-tract infections, related antibiotics and PCa, whilst adjusting for civil status, education, Charlson Comorbidity Index and time between lower urinary-tract infection and PCa diagnosis. It was found that lower urinary-tract infections did not affect PCa risk, however, having a lower urinary-tract infection or a first antibiotic prescription 6-12 months before PCa were both associated with an increased risk of PCa (OR: 1.50, 95% CI: 1.23-1.82 and 1.96, 1.71-2.25, respectively), as compared to men without lower urinary-tract infections. Compared to men with no prescriptions for antibiotics, men who were prescribed ≥10 antibiotics, were 15% less likely to develop PCa (OR: 0.85, 95% CI: 0.78-0.91). PCa was not found to be associated with diagnosis of a urinary-tract infection or frequency, but was positively associated with short time since diagnoses of lower urinary-tract infection or receiving prescriptions for antibiotics. These observations can likely be explained by detection bias, which highlights the importance of data on the diagnostic work-up when studying potential risk factors for PCa.

Measurement of empathy among Argentine cardiologists: Psychometrics and differences by age, gender, and subspecialty.

PubMed

Borracci, Raúl Alfredo; Doval, Hernán C; Nuñez, Carmen; Samarelli, Marisa; Tamini, Susana; Tanus, Eduardo

2015-01-01

Cardiologists are involved in the management of patients with multiple cardiovascular risk factors and chronic heart diseases, so empathy is a necessary feature to deal with them. The aim of the study was to evaluate the validity and reliability of the Spanish version of the Jefferson Scale of Physician Empathy (JSPE) among Argentine cardiologists and to explore the potential differences by age, gender, and subspecialty. Between August and September 2012, we performed a survey in a non-randomized sample of 566 Spanish-speaking cardiologists of Argentina. A Principle Component Analysis (PCA) was used to explore the link between observed variables and latent variables in order to identify the factor structure. The PCA criteria for identifying the factor structure were examined with the Kaiser-Meyer-Olkin (KMO) analysis. The KMO measure of sampling adequacy was 0.86 and Bartlett's test of sphericity was highly significant (p = 0.000), determining the suitability of the data set for factor analysis. The PCA of 20 items yielded a three factor model that accounted for 40.6% of the variance. The JSPE mean rank score for women was 307.9 vs. 275.0 for men (p = 0.017). The comparison of mean rank score according to age (quartiles) showed a significant relation between older age and empathy. No difference was found when the mean rank scores were compared by respondent subspecialty. JSPE provides a valid and reliable scale to measure Argentine cardiologists' attitudes towards empathy. Female cardiologists seem to be more empathic than their male colleagues, and a positive relationship between age and empathy was found.

Investigation of probabilistic principal component analysis compared to proper orthogonal decomposition methods for basis extraction and missing data estimation

NASA Astrophysics Data System (ADS)

Lee, Kyunghoon

To evaluate the maximum likelihood estimates (MLEs) of probabilistic principal component analysis (PPCA) parameters such as a factor-loading, PPCA can invoke an expectation-maximization (EM) algorithm, yielding an EM algorithm for PPCA (EM-PCA). In order to examine the benefits of the EM-PCA for aerospace engineering applications, this thesis attempts to qualitatively and quantitatively scrutinize the EM-PCA alongside both POD and gappy POD using high-dimensional simulation data. In pursuing qualitative investigations, the theoretical relationship between POD and PPCA is transparent such that the factor-loading MLE of PPCA, evaluated by the EM-PCA, pertains to an orthogonal basis obtained by POD. By contrast, the analytical connection between gappy POD and the EM-PCA is nebulous because they distinctively approximate missing data due to their antithetical formulation perspectives: gappy POD solves a least-squares problem whereas the EM-PCA relies on the expectation of the observation probability model. To juxtapose both gappy POD and the EM-PCA, this research proposes a unifying least-squares perspective that embraces the two disparate algorithms within a generalized least-squares framework. As a result, the unifying perspective reveals that both methods address similar least-squares problems; however, their formulations contain dissimilar bases and norms. Furthermore, this research delves into the ramifications of the different bases and norms that will eventually characterize the traits of both methods. To this end, two hybrid algorithms of gappy POD and the EM-PCA are devised and compared to the original algorithms for a qualitative illustration of the different basis and norm effects. After all, a norm reflecting a curve-fitting method is found to more significantly affect estimation error reduction than a basis for two example test data sets: one is absent of data only at a single snapshot and the other misses data across all the snapshots. From a numerical performance aspect, the EM-PCA is computationally less efficient than POD for intact data since it suffers from slow convergence inherited from the EM algorithm. For incomplete data, this thesis quantitatively found that the number of data missing snapshots predetermines whether the EM-PCA or gappy POD outperforms the other because of the computational cost of a coefficient evaluation, resulting from a norm selection. For instance, gappy POD demands laborious computational effort in proportion to the number of data-missing snapshots as a consequence of the gappy norm. In contrast, the computational cost of the EM-PCA is invariant to the number of data-missing snapshots thanks to the L2 norm. In general, the higher the number of data-missing snapshots, the wider the gap between the computational cost of gappy POD and the EM-PCA. Based on the numerical experiments reported in this thesis, the following criterion is recommended regarding the selection between gappy POD and the EM-PCA for computational efficiency: gappy POD for an incomplete data set containing a few data-missing snapshots and the EM-PCA for an incomplete data set involving multiple data-missing snapshots. Last, the EM-PCA is applied to two aerospace applications in comparison to gappy POD as a proof of concept: one with an emphasis on basis extraction and the other with a focus on missing data reconstruction for a given incomplete data set with scattered missing data. The first application exploits the EM-PCA to efficiently construct reduced-order models of engine deck responses obtained by the numerical propulsion system simulation (NPSS), some of whose results are absent due to failed analyses caused by numerical instability. Model-prediction tests validate that engine performance metrics estimated by the reduced-order NPSS model exhibit considerably good agreement with those directly obtained by NPSS. Similarly, the second application illustrates that the EM-PCA is significantly more cost effective than gappy POD at repairing spurious PIV measurements obtained from acoustically-excited, bluff-body jet flow experiments. The EM-PCA reduces computational cost on factors 8 ˜ 19 compared to gappy POD while generating the same restoration results as those evaluated by gappy POD. All in all, through comprehensive theoretical and numerical investigation, this research establishes that the EM-PCA is an efficient alternative to gappy POD for an incomplete data set containing missing data over an entire data set. (Abstract shortened by UMI.)

Spatial Mapping of Pyocyanin in Pseudomonas aeruginosa Bacterial Communities by Surface Enhanced Raman Scattering

PubMed Central

Polisetti, Sneha; Baig, Nameera F.; Morales-Soto, Nydia; Shrout, Joshua D.; Bohn, Paul W.

2017-01-01

Surface Enhanced Raman Spectroscopy (SERS) imaging was used in conjunction with Principal Component Analysis (PCA) for the in situ spatiotemporal mapping of the virulence factor pyocyanin, in communities of the pathogenic bacterium Pseudomonas aeruginosa. The combination of SERS imaging and PCA analysis provides a robust method for characterization of heterogeneous biological systems while circumventing issues associated with interference from sample autofluorescence and low reproducibility of SERS signals. The production of pyocyanin is found to depend both on the growth carbon source and on the specific strain of P. aeruginosa studied. A cystic fibrosis lung isolate strain of P. aeruginosa synthesizes and secretes pyocyanin when grown with glucose and glutamate, while the laboratory strain exhibits detectable production of pyocyanin only when grown with glutamate as the source of carbon. Pyocyanin production in the laboratory strain grown with glucose was below the limit of detection of SERS. In addition, the combination of SERS imaging and PCA can elucidate subtle differences in the molecular composition of biofilms. PCA loading plots from the clinical isolate exhibit features corresponding to vibrational bands of carbohydrates, which represent the mucoid biofilm matrix specific to that isolate, features that are not seen in the PCA loading plots of the laboratory strain. PMID:27354400

The function of oxytocin: a potential biomarker for prostate cancer diagnosis and promoter of prostate cancer.

PubMed

Xu, Huan; Fu, Shi; Chen, Qi; Gu, Meng; Zhou, Juan; Liu, Chong; Chen, Yanbo; Wang, Zhong

2017-05-09

To measure the level of oxytocin in serum and prostate cancer (PCa) tissue and study its effect on the proliferation of PCa cells. Oxytocin level in serum was significantly increased in PCa patients compared with the no-carcinoma individuals. Additionally, the levels of oxytocin and its receptor were also elevated in the PCa tissue. However, no significant difference existed among the PCa of various Gleason grades. Western blot analysis confirmed the previous results and revealed an increased expression level of APPL1. The level of oxytocin in serum was measured by ELISA analysis. The expression of oxytocin and its receptor in prostate was analyzed by immunohistochemistry. The proliferation and apoptosis of PCa cells were assessed by the Cell Counting Kit 8 (CCK8) assay, cell cycle analysis and caspase3 activity analysis, respectively. Western blot analysis was used for the detection of PCNA, Caspase3 and APPL1 protein levels. Serum and prostatic oxytocin levels are increased in the PCa subjects. Serum oxytocin level may be a biomarker for PCa in the future. Oxytocin increases PCa growth and APPL1 expression.

An Efficient Taguchi Approach for the Performance Optimization of Health, Safety, Environment and Ergonomics in Generation Companies.

PubMed

Azadeh, Ali; Sheikhalishahi, Mohammad

2015-06-01

A unique framework for performance optimization of generation companies (GENCOs) based on health, safety, environment, and ergonomics (HSEE) indicators is presented. To rank this sector of industry, the combination of data envelopment analysis (DEA), principal component analysis (PCA), and Taguchi are used for all branches of GENCOs. These methods are applied in an integrated manner to measure the performance of GENCO. The preferred model between DEA, PCA, and Taguchi is selected based on sensitivity analysis and maximum correlation between rankings. To achieve the stated objectives, noise is introduced into input data. The results show that Taguchi outperforms other methods. Moreover, a comprehensive experiment is carried out to identify the most influential factor for ranking GENCOs. The approach developed in this study could be used for continuous assessment and improvement of GENCO's performance in supplying energy with respect to HSEE factors. The results of such studies would help managers to have better understanding of weak and strong points in terms of HSEE factors.

Potentiation of Inflammatory CXCL8 Signalling Sustains Cell Survival in PTEN-deficient Prostate Carcinoma

PubMed Central

Maxwell, Pamela J.; Coulter, Jonathan; Walker, Steven M.; McKechnie, Melanie; Neisen, Jessica; McCabe, Nuala; Kennedy, Richard D.; Salto-Tellez, Manuel; Albanese, Chris; Waugh, David J.J.

2014-01-01

Background: Inflammation and genetic instability are enabling characteristics of prostate carcinoma (PCa). Inactivation of the tumour suppressor gene phosphatase and tensin homolog (PTEN) is prevalent in early PCa. The relationship of PTEN deficiency to inflammatory signalling remains to be characterised. Objective: To determine how loss of PTEN functionality modulates expression and efficacy of clinically relevant, proinflammatory chemokines in PCa. Design, setting, and participants: Experiments were performed in established cell-based PCa models, supported by pathologic analysis of chemokine expression in prostate tissue harvested from PTEN heterozygous (Pten+/−) mice harbouring inactivation of one PTEN allele. Interventions: Small interfering RNA (siRNA)–or small hairpin RNA (shRNA)–directed strategies were used to repress PTEN expression and resultant interleukin-8 (CXCL8) signalling, determined under normal and hypoxic culture conditions. Outcome measurements and statistical analysis: Changes in chemokine expression in PCa cells and tissue were analysed by real-time polymerase chain reaction (PCR), immunoblotting, enzyme-linked immunosorbent assay (ELISA), and immunohistochemistry; effects of chemokine signalling on cell function were assessed by cell cycle analysis, apoptosis, and survival assays. Results and limitations: Transient (siRNA) or prolonged (shRNA) PTEN repression increased expression of CXCL8 and its receptors, chemokine (C-X-C motif) receptor (CXCR) 1 and CXCR2, in PCa cells. Hypoxia-induced increases in CXCL8, CXCR1, and CXCR2 expression were greater in magnitude and duration in PTEN-depleted cells. Autocrine CXCL8 signalling was more efficacious in PTEN-depleted cells, inducing hypoxia-inducible factor-1 (HIF-1) and nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) transcription and regulating genes involved in survival and angiogenesis. Increased expression of the orthologous chemokine KC was observed in regions displaying atypical cytologic features in Pten+/− murine prostate tissue relative to normal epithelium in wild-type PTEN (PtenWT) glands. Attenuation of CXCL8 signalling decreased viability of PCa cells harbouring partial or complete PTEN loss through promotion of G1 cell cycle arrest and apoptosis. The current absence of clinical validation is a limitation of the study. Conclusions: PTEN loss induces a selective upregulation of CXCL8 signalling that sustains the growth and survival of PTEN-deficient prostate epithelium. PMID:22939387

Principal component analysis of dietary and lifestyle patterns in relation to risk of subtypes of esophageal and gastric cancer

PubMed Central

Silvera, Stephanie A. Navarro; Mayne, Susan T; Risch, Harvey A.; Gammon, Marilie D; Vaughan, Thomas; Chow, Wong-Ho; Dubin, Joel A; Dubrow, Robert; Schoenberg, Janet; Stanford, Janet L; West, A. Brian; Rotterdam, Heidrun; Blot, William J

2011-01-01

Purpose To perform pattern analyses of dietary and lifestyle factors in relation to risk of esophageal and gastric cancers. Methods We evaluated risk factors for esophageal adenocarcinoma (EA), esophageal squamous cell carcinoma (ESCC), gastric cardia adenocarcinoma (GCA), and other gastric cancers (OGA) using data from a population-based case-control study conducted in Connecticut, New Jersey, and western Washington state. Dietary/lifestyle patterns were created using principal component analysis (PCA). Impact of the resultant scores on cancer risk was estimated through logistic regression. Results PCA identified six patterns: meat/nitrite, fruit/vegetable, smoking/alcohol, legume/meat alternate, GERD/BMI, and fish/vitamin C. Risk of each cancer under study increased with rising meat/nitrite score. Risk of EA increased with increasing GERD/BMI score, and risk of ESCC rose with increasing smoking/alcohol score and decreasing GERD/BMI score. Fruit/vegetable scores were inversely associated with EA, ESCC, and GCA. Conclusions PCA may provide a useful approach for summarizing extensive dietary/lifestyle data into fewer interpretable combinations that discriminate between cancer cases and controls. The analyses suggest that meat/nitrite intake is associated with elevated risk of each cancer under study, while fruit/vegetable intake reduces risk of EA, ESCC, and GCA. GERD/obesity were confirmed as risk factors for EA and smoking/alcohol as risk factors for ESCC. PMID:21435900

The Network Structure of Human Personality According to the NEO-PI-R: Matching Network Community Structure to Factor Structure

PubMed Central

Goekoop, Rutger; Goekoop, Jaap G.; Scholte, H. Steven

2012-01-01

Introduction Human personality is described preferentially in terms of factors (dimensions) found using factor analysis. An alternative and highly related method is network analysis, which may have several advantages over factor analytic methods. Aim To directly compare the ability of network community detection (NCD) and principal component factor analysis (PCA) to examine modularity in multidimensional datasets such as the neuroticism-extraversion-openness personality inventory revised (NEO-PI-R). Methods 434 healthy subjects were tested on the NEO-PI-R. PCA was performed to extract factor structures (FS) of the current dataset using both item scores and facet scores. Correlational network graphs were constructed from univariate correlation matrices of interactions between both items and facets. These networks were pruned in a link-by-link fashion while calculating the network community structure (NCS) of each resulting network using the Wakita Tsurumi clustering algorithm. NCSs were matched against FS and networks of best matches were kept for further analysis. Results At facet level, NCS showed a best match (96.2%) with a ‘confirmatory’ 5-FS. At item level, NCS showed a best match (80%) with the standard 5-FS and involved a total of 6 network clusters. Lesser matches were found with ‘confirmatory’ 5-FS and ‘exploratory’ 6-FS of the current dataset. Network analysis did not identify facets as a separate level of organization in between items and clusters. A small-world network structure was found in both item- and facet level networks. Conclusion We present the first optimized network graph of personality traits according to the NEO-PI-R: a ‘Personality Web’. Such a web may represent the possible routes that subjects can take during personality development. NCD outperforms PCA by producing plausible modularity at item level in non-standard datasets, and can identify the key roles of individual items and clusters in the network. PMID:23284713

The network structure of human personality according to the NEO-PI-R: matching network community structure to factor structure.

PubMed

Goekoop, Rutger; Goekoop, Jaap G; Scholte, H Steven

2012-01-01

Human personality is described preferentially in terms of factors (dimensions) found using factor analysis. An alternative and highly related method is network analysis, which may have several advantages over factor analytic methods. To directly compare the ability of network community detection (NCD) and principal component factor analysis (PCA) to examine modularity in multidimensional datasets such as the neuroticism-extraversion-openness personality inventory revised (NEO-PI-R). 434 healthy subjects were tested on the NEO-PI-R. PCA was performed to extract factor structures (FS) of the current dataset using both item scores and facet scores. Correlational network graphs were constructed from univariate correlation matrices of interactions between both items and facets. These networks were pruned in a link-by-link fashion while calculating the network community structure (NCS) of each resulting network using the Wakita Tsurumi clustering algorithm. NCSs were matched against FS and networks of best matches were kept for further analysis. At facet level, NCS showed a best match (96.2%) with a 'confirmatory' 5-FS. At item level, NCS showed a best match (80%) with the standard 5-FS and involved a total of 6 network clusters. Lesser matches were found with 'confirmatory' 5-FS and 'exploratory' 6-FS of the current dataset. Network analysis did not identify facets as a separate level of organization in between items and clusters. A small-world network structure was found in both item- and facet level networks. We present the first optimized network graph of personality traits according to the NEO-PI-R: a 'Personality Web'. Such a web may represent the possible routes that subjects can take during personality development. NCD outperforms PCA by producing plausible modularity at item level in non-standard datasets, and can identify the key roles of individual items and clusters in the network.

Relative importance of habitat filtering and limiting similarity on species assemblages of alpine and subalpine plant communities.

PubMed

Takahashi, Koichi; Tanaka, Saeka

2016-11-01

This study examined how habitat filtering and limiting similarity affect species assemblages of alpine and subalpine plant communities along a slope gradient on Mt. Norikura in central Japan. Plant traits (plant height, individual leaf area, specific leaf area (SLA), leaf linearity, leaf nitrogen and chlorophyll concentrations) and abiotic environmental factors (elevation, slope inclination, ground surface texture, soil water, soil pH, soil nutrient concentrations of NH 4 -N and NO 3 -N) were examined. The metrics of variance, range, kurtosis and the standard deviation of neighbor distance divided by the range of traits present (SDNDr) were calculated for each plant trait to measure trait distribution patterns. Limiting similarity was detected only for chlorophyll concentration. By contrast, habitat filtering was detected for individual leaf area, SLA, leaf linearity, chlorophyll concentration. Abiotic environmental factors were summarized by the principal component analysis (PCA). The first PCA axis positively correlated with elevation and soil pH, and negatively correlated with sand cover, soil water, NH 4 -N and NO 3 -N concentrations. High values of the first PCA axis represent the wind-exposed upper slope with lower soil moisture and nutrient availabilities. Plant traits changed along the first PCA axis. Leaf area, SLA and chlorophyll concentration decreased, and leaf linearity increased with the first PCA axis. This study showed that the species assemblage of alpine and subalpine plants was determined mainly by habitat filtering, indicating that abiotic environmental factors are more important for species assemblage than interspecific competition. Therefore, only species adapting to abiotic environments can distribute to these environments.

Mapping brain activity in gradient-echo functional MRI using principal component analysis

NASA Astrophysics Data System (ADS)

Khosla, Deepak; Singh, Manbir; Don, Manuel

1997-05-01

The detection of sites of brain activation in functional MRI has been a topic of immense research interest and many technique shave been proposed to this end. Recently, principal component analysis (PCA) has been applied to extract the activated regions and their time course of activation. This method is based on the assumption that the activation is orthogonal to other signal variations such as brain motion, physiological oscillations and other uncorrelated noises. A distinct advantage of this method is that it does not require any knowledge of the time course of the true stimulus paradigm. This technique is well suited to EPI image sequences where the sampling rate is high enough to capture the effects of physiological oscillations. In this work, we propose and apply tow methods that are based on PCA to conventional gradient-echo images and investigate their usefulness as tools to extract reliable information on brain activation. The first method is a conventional technique where a single image sequence with alternating on and off stages is subject to a principal component analysis. The second method is a PCA-based approach called the common spatial factor analysis technique (CSF). As the name suggests, this method relies on common spatial factors between the above fMRI image sequence and a background fMRI. We have applied these methods to identify active brain ares during visual stimulation and motor tasks. The results from these methods are compared to those obtained by using the standard cross-correlation technique. We found good agreement in the areas identified as active across all three techniques. The results suggest that PCA and CSF methods have good potential in detecting the true stimulus correlated changes in the presence of other interfering signals.

Multimethod prediction of physical parent-child aggression risk in expectant mothers and fathers with Social Information Processing theory.

PubMed

Rodriguez, Christina M; Smith, Tamika L; Silvia, Paul J

2016-01-01

The Social Information Processing (SIP) model postulates that parents undergo a series of stages in implementing physical discipline that can escalate into physical child abuse. The current study utilized a multimethod approach to investigate whether SIP factors can predict risk of parent-child aggression (PCA) in a diverse sample of expectant mothers and fathers. SIP factors of PCA attitudes, negative child attributions, reactivity, and empathy were considered as potential predictors of PCA risk; additionally, analyses considered whether personal history of PCA predicted participants' own PCA risk through its influence on their attitudes and attributions. Findings indicate that, for both mothers and fathers, history influenced attitudes but not attributions in predicting PCA risk, and attitudes and attributions predicted PCA risk; empathy and reactivity predicted negative child attributions for expectant mothers, but only reactivity significantly predicted attributions for expectant fathers. Path models for expectant mothers and fathers were remarkably similar. Overall, the findings provide support for major aspects of the SIP model. Continued work is needed in studying the progression of these factors across time for both mothers and fathers as well as the inclusion of other relevant ecological factors to the SIP model. Copyright © 2015 Elsevier Ltd. All rights reserved.

An application of principal component analysis to the clavicle and clavicle fixation devices.

PubMed

Daruwalla, Zubin J; Courtis, Patrick; Fitzpatrick, Clare; Fitzpatrick, David; Mullett, Hannan

2010-03-26

Principal component analysis (PCA) enables the building of statistical shape models of bones and joints. This has been used in conjunction with computer assisted surgery in the past. However, PCA of the clavicle has not been performed. Using PCA, we present a novel method that examines the major modes of size and three-dimensional shape variation in male and female clavicles and suggests a method of grouping the clavicle into size and shape categories. Twenty-one high-resolution computerized tomography scans of the clavicle were reconstructed and analyzed using a specifically developed statistical software package. After performing statistical shape analysis, PCA was applied to study the factors that account for anatomical variation. The first principal component representing size accounted for 70.5 percent of anatomical variation. The addition of a further three principal components accounted for almost 87 percent. Using statistical shape analysis, clavicles in males have a greater lateral depth and are longer, wider and thicker than in females. However, the sternal angle in females is larger than in males. PCA confirmed these differences between genders but also noted that men exhibit greater variance and classified clavicles into five morphological groups. This unique approach is the first that standardizes a clavicular orientation. It provides information that is useful to both, the biomedical engineer and clinician. Other applications include implant design with regard to modifying current or designing future clavicle fixation devices. Our findings support the need for further development of clavicle fixation devices and the questioning of whether gender-specific devices are necessary.

A case-control study of lower urinary-tract infections, associated antibiotics and the risk of developing prostate cancer using PCBaSe 3.0

PubMed Central

Garmo, Hans; Beckmann, Kerri; Stattin, Pär; Adolfsson, Jan; Van Hemelrijck, Mieke

2018-01-01

Objectives To investigate the association between lower urinary-tract infections, their associated antibiotics and the subsequent risk of developing PCa. Subjects/Patients (or materials) and methods Using data from the Swedish PCBaSe 3.0, we performed a matched case-control study (8762 cases and 43806 controls). Conditional logistic regression analysis was used to assess the association between lower urinary-tract infections, related antibiotics and PCa, whilst adjusting for civil status, education, Charlson Comorbidity Index and time between lower urinary-tract infection and PCa diagnosis. Results It was found that lower urinary-tract infections did not affect PCa risk, however, having a lower urinary-tract infection or a first antibiotic prescription 6–12 months before PCa were both associated with an increased risk of PCa (OR: 1.50, 95% CI: 1.23–1.82 and 1.96, 1.71–2.25, respectively), as compared to men without lower urinary-tract infections. Compared to men with no prescriptions for antibiotics, men who were prescribed ≥10 antibiotics, were 15% less likely to develop PCa (OR: 0.85, 95% CI: 0.78–0.91). Conclusion PCa was not found to be associated with diagnosis of a urinary-tract infection or frequency, but was positively associated with short time since diagnoses of lower urinary-tract infection or receiving prescriptions for antibiotics. These observations can likely be explained by detection bias, which highlights the importance of data on the diagnostic work-up when studying potential risk factors for PCa. PMID:29649268

The language profile of Posterior Cortical Atrophy

PubMed Central

Crutch, Sebastian J.; Lehmann, Manja; Warren, Jason D.; Rohrer, Jonathan D.

2015-01-01

Background Posterior Cortical Atrophy (PCA) is typically considered to be a visual syndrome, primarily characterised by progressive impairment of visuoperceptual and visuospatial skills. However patients commonly describe early difficulties with word retrieval. This paper details the first systematic analysis of linguistic function in PCA. Characterising and quantifying the aphasia associated with PCA is important for clarifying diagnostic and selection criteria for clinical and research studies. Methods Fifteen patients with PCA, 7 patients with logopenic/phonological aphasia (LPA) and 18 age-matched healthy participants completed a detailed battery of linguistic tests evaluating auditory input processing, repetition and working memory, lexical and grammatical comprehension, single word retrieval and fluency, and spontaneous speech. Results Relative to healthy controls, PCA patients exhibited language impairments across all the domains examined, but with anomia, reduced phonemic fluency and slowed speech rate the most prominent deficits. PCA performance most closely resembled that of LPA patients on tests of auditory input processing, repetition and digit span, but was relatively stronger on tasks of comprehension and spontaneous speech. Conclusions The study demonstrates that in addition to the well-reported degradation of vision, literacy and numeracy, PCA is characterised by a progressive oral language dysfunction with prominent word retrieval difficulties. Overlap in the linguistic profiles of PCA and LPA, which are both most commonly caused by Alzheimer’s disease, further emphasises the notion of a phenotypic continuum between typical and atypical manifestations of the disease. Clarifying the boundaries between AD phenotypes has important implications for diagnosis, clinical trial recruitment and investigations into biological factors driving phenotypic heterogeneity in AD. Rehabilitation strategies to ameliorate the phonological deficit in PCA are required. PMID:23138762

A Study of Wind Turbine Comprehensive Operational Assessment Model Based on EM-PCA Algorithm

NASA Astrophysics Data System (ADS)

Zhou, Minqiang; Xu, Bin; Zhan, Yangyan; Ren, Danyuan; Liu, Dexing

2018-01-01

To assess wind turbine performance accurately and provide theoretical basis for wind farm management, a hybrid assessment model based on Entropy Method and Principle Component Analysis (EM-PCA) was established, which took most factors of operational performance into consideration and reach to a comprehensive result. To verify the model, six wind turbines were chosen as the research objects, the ranking obtained by the method proposed in the paper were 4#>6#>1#>5#>2#>3#, which are completely in conformity with the theoretical ranking, which indicates that the reliability and effectiveness of the EM-PCA method are high. The method could give guidance for processing unit state comparison among different units and launching wind farm operational assessment.

Characterization and source identification of pollutants in runoff from a mixed land use watershed using ordination analyses.

PubMed

Lee, Dong Hoon; Kim, Jin Hwi; Mendoza, Joseph A; Lee, Chang Hee; Kang, Joo-Hyon

2016-05-01

While identification of critical pollutant sources is the key initial step for cost-effective runoff management, it is challenging due to the highly uncertain nature of runoff pollution, especially during a storm event. To identify critical sources and their quantitative contributions to runoff pollution (especially focusing on phosphorous), two ordination methods were used in this study: principal component analysis (PCA) and positive matrix factorization (PMF). For the ordination analyses, we used runoff quality data for 14 storm events, including data for phosphorus, 11 heavy metal species, and eight ionic species measured at the outlets of subcatchments with different land use compositions in a mixed land use watershed. Five factors as sources of runoff pollutants were identified by PCA: agrochemicals, groundwater, native soils, domestic sewage, and urban sources (building materials and automotive activities). PMF identified similar factors to those identified by PCA, with more detailed source mechanisms for groundwater (i.e., nitrate leaching and cation exchange) and urban sources (vehicle components/motor oils/building materials and vehicle exhausts), confirming the sources identified by PCA. PMF was further used to quantify contributions of the identified sources to the water quality. Based on the results, agrochemicals and automotive activities were the two dominant and ubiquitous phosphorus sources (39-61 and 16-47 %, respectively) in the study area, regardless of land use types.

Evidence for Masturbation and Prostate Cancer Risk: Do We Have a Verdict?

PubMed

Aboul-Enein, Basil H; Bernstein, Joshua; Ross, Michael W

2016-07-01

Prostate cancer (PCa) is one of the leading causes of cancer death in men and remains one of the most diagnosed malignancies worldwide. Ongoing public health efforts continue to promote protective factors, such as diet, physical activity, and other lifestyle modifications, against PCa development. Masturbation is a nearly universal safe sexual activity that transcends societal boundaries and geography yet continues to be met with stigma and controversy in contemporary society. Although previous studies have examined associations between sexual activity and PCa risk, anecdotal relations have been suggested regarding masturbation practice and PCa risk. To provide a summary of the published literature and examine the contemporary evidence for relations between masturbation practice and PCa risk. A survey of the current literature using seven academic electronic databases was conducted using search terms and key words associated with masturbation practice and PCa risk. The practice of masturbation and its relation to PCa risk. The literature search identified study samples (n = 16) published before October 2015. Sample inclusions varied by study type, sample size, and primary objective. Protective relations (n = 7) between ejaculation through masturbation and PCa risk were reported by 44% of the study sample. Age range emerged as a significant variable in the relation between masturbation and PCa. Findings included relations among masturbation, ejaculation frequency, and age range as individual factors of PCa risk. No universally accepted themes were identified across the study sample. Throughout the sample, there was insufficient agreement in survey design and data reporting. Potential avenues for new research include frequency of ejaculation and age range as covarying factors that could lead to more definitive statements about masturbation practice and PCa risk. Copyright © 2016 International Society for Sexual Medicine. Published by Elsevier Inc. All rights reserved.

Prostate extracellular vesicles in patient plasma as a liquid biopsy platform for prostate cancer using nanoscale flow cytometry.

PubMed

Biggs, Colleen N; Siddiqui, Khurram M; Al-Zahrani, Ali A; Pardhan, Siddika; Brett, Sabine I; Guo, Qiu Q; Yang, Jun; Wolf, Philipp; Power, Nicholas E; Durfee, Paul N; MacMillan, Connor D; Townson, Jason L; Brinker, Jeffrey C; Fleshner, Neil E; Izawa, Jonathan I; Chambers, Ann F; Chin, Joseph L; Leong, Hon S

2016-02-23

Extracellular vesicles released by prostate cancer present in seminal fluid, urine, and blood may represent a non-invasive means to identify and prioritize patients with intermediate risk and high risk of prostate cancer. We hypothesize that enumeration of circulating prostate microparticles (PMPs), a type of extracellular vesicle (EV), can identify patients with Gleason Score≥4+4 prostate cancer (PCa) in a manner independent of PSA. Plasmas from healthy volunteers, benign prostatic hyperplasia patients, and PCa patients with various Gleason score patterns were analyzed for PMPs. We used nanoscale flow cytometry to enumerate PMPs which were defined as submicron events (100-1000nm) immunoreactive to anti-PSMA mAb when compared to isotype control labeled samples. Levels of PMPs (counts/µL of plasma) were also compared to CellSearch CTC Subclasses in various PCa metastatic disease subtypes (treatment naïve, castration resistant prostate cancer) and in serially collected plasma sets from patients undergoing radical prostatectomy. PMP levels in plasma as enumerated by nanoscale flow cytometry are effective in distinguishing PCa patients with Gleason Score≥8 disease, a high-risk prognostic factor, from patients with Gleason Score≤7 PCa, which carries an intermediate risk of PCa recurrence. PMP levels were independent of PSA and significantly decreased after surgical resection of the prostate, demonstrating its prognostic potential for clinical follow-up. CTC subclasses did not decrease after prostatectomy and were not effective in distinguishing localized PCa patients from metastatic PCa patients. PMP enumeration was able to identify patients with Gleason Score ≥8 PCa but not patients with Gleason Score 4+3 PCa, but offers greater confidence than CTC counts in identifying patients with metastatic prostate cancer. CTC Subclass analysis was also not effective for post-prostatectomy follow up and for distinguishing metastatic PCa and localized PCa patients. Nanoscale flow cytometry of PMPs presents an emerging biomarker platform for various stages of prostate cancer.

Prostate extracellular vesicles in patient plasma as a liquid biopsy platform for prostate cancer using nanoscale flow cytometry

PubMed Central

Al-Zahrani, Ali A.; Pardhan, Siddika; Brett, Sabine I.; Guo, Qiu Q.; Yang, Jun; Wolf, Philipp; Power, Nicholas E.; Durfee, Paul N.; MacMillan, Connor D.; Townson, Jason L.; Brinker, Jeffrey C.; Fleshner, Neil E.; Izawa, Jonathan I.; Chambers, Ann F.; Chin, Joseph L.; Leong, Hon S.

2016-01-01

Background Extracellular vesicles released by prostate cancer present in seminal fluid, urine, and blood may represent a non-invasive means to identify and prioritize patients with intermediate risk and high risk of prostate cancer. We hypothesize that enumeration of circulating prostate microparticles (PMPs), a type of extracellular vesicle (EV), can identify patients with Gleason Score≥4+4 prostate cancer (PCa) in a manner independent of PSA. Patients and Methods Plasmas from healthy volunteers, benign prostatic hyperplasia patients, and PCa patients with various Gleason score patterns were analyzed for PMPs. We used nanoscale flow cytometry to enumerate PMPs which were defined as submicron events (100-1000nm) immunoreactive to anti-PSMA mAb when compared to isotype control labeled samples. Levels of PMPs (counts/μL of plasma) were also compared to CellSearch CTC Subclasses in various PCa metastatic disease subtypes (treatment naïve, castration resistant prostate cancer) and in serially collected plasma sets from patients undergoing radical prostatectomy. Results PMP levels in plasma as enumerated by nanoscale flow cytometry are effective in distinguishing PCa patients with Gleason Score≥8 disease, a high-risk prognostic factor, from patients with Gleason Score≤7 PCa, which carries an intermediate risk of PCa recurrence. PMP levels were independent of PSA and significantly decreased after surgical resection of the prostate, demonstrating its prognostic potential for clinical follow-up. CTC subclasses did not decrease after prostatectomy and were not effective in distinguishing localized PCa patients from metastatic PCa patients. Conclusions PMP enumeration was able to identify patients with Gleason Score ≥8 PCa but not patients with Gleason Score 4+3 PCa, but offers greater confidence than CTC counts in identifying patients with metastatic prostate cancer. CTC Subclass analysis was also not effective for post-prostatectomy follow up and for distinguishing metastatic PCa and localized PCa patients. Nanoscale flow cytometry of PMPs presents an emerging biomarker platform for various stages of prostate cancer. PMID:26814433

Principal component analysis of normalized full spectrum mass spectrometry data in multiMS-toolbox: An effective tool to identify important factors for classification of different metabolic patterns and bacterial strains.

PubMed

Cejnar, Pavel; Kuckova, Stepanka; Prochazka, Ales; Karamonova, Ludmila; Svobodova, Barbora

2018-06-15

Explorative statistical analysis of mass spectrometry data is still a time-consuming step. We analyzed critical factors for application of principal component analysis (PCA) in mass spectrometry and focused on two whole spectrum based normalization techniques and their application in the analysis of registered peak data and, in comparison, in full spectrum data analysis. We used this technique to identify different metabolic patterns in the bacterial culture of Cronobacter sakazakii, an important foodborne pathogen. Two software utilities, the ms-alone, a python-based utility for mass spectrometry data preprocessing and peak extraction, and the multiMS-toolbox, an R software tool for advanced peak registration and detailed explorative statistical analysis, were implemented. The bacterial culture of Cronobacter sakazakii was cultivated on Enterobacter sakazakii Isolation Agar, Blood Agar Base and Tryptone Soya Agar for 24 h and 48 h and applied by the smear method on an Autoflex speed MALDI-TOF mass spectrometer. For three tested cultivation media only two different metabolic patterns of Cronobacter sakazakii were identified using PCA applied on data normalized by two different normalization techniques. Results from matched peak data and subsequent detailed full spectrum analysis identified only two different metabolic patterns - a cultivation on Enterobacter sakazakii Isolation Agar showed significant differences to the cultivation on the other two tested media. The metabolic patterns for all tested cultivation media also proved the dependence on cultivation time. Both whole spectrum based normalization techniques together with the full spectrum PCA allow identification of important discriminative factors in experiments with several variable condition factors avoiding any problems with improper identification of peaks or emphasis on bellow threshold peak data. The amounts of processed data remain still manageable. Both implemented software utilities are available free of charge from http://uprt.vscht.cz/ms. Copyright © 2018 John Wiley & Sons, Ltd.

Analysis of factors affecting the accuracy, reproducibility, and interpretation of microbial community carbon source utilization patterns

USGS Publications Warehouse

Haack, S.K.; Garchow, H.; Klug, M.J.; Forney, L.J.

1995-01-01

We determined factors that affect responses of bacterial isolates and model bacterial communities to the 95 carbon substrates in Biolog microliter plates. For isolates and communities of three to six bacterial strains, substrate oxidation rates were typically nonlinear and were delayed by dilution of the inoculum. When inoculum density was controlled, patterns of positive and negative responses exhibited by microbial communities to each of the carbon sources were reproducible. Rates and extents of substrate oxidation by the communities were also reproducible but were not simply the sum of those exhibited by community members when tested separately. Replicates of the same model community clustered when analyzed by principal- components analysis (PCA), and model communities with different compositions were clearly separated un the first PCA axis, which accounted for >60% of the dataset variation. PCA discrimination among different model communities depended on the extent to which specific substrates were oxidized. However, the substrates interpreted by PCA to be most significant in distinguishing the communities changed with reading time, reflecting the nonlinearity of substrate oxidation rates. Although whole-community substrate utilization profiles were reproducible signatures for a given community, the extent of oxidation of specific substrates and the numbers or activities of microorganisms using those substrates in a given community were not correlated. Replicate soil samples varied significantly in the rate and extent of oxidation of seven tested substrates, suggesting microscale heterogeneity in composition of the soil microbial community.

Exploring patterns enriched in a dataset with contrastive principal component analysis.

PubMed

Abid, Abubakar; Zhang, Martin J; Bagaria, Vivek K; Zou, James

2018-05-30

Visualization and exploration of high-dimensional data is a ubiquitous challenge across disciplines. Widely used techniques such as principal component analysis (PCA) aim to identify dominant trends in one dataset. However, in many settings we have datasets collected under different conditions, e.g., a treatment and a control experiment, and we are interested in visualizing and exploring patterns that are specific to one dataset. This paper proposes a method, contrastive principal component analysis (cPCA), which identifies low-dimensional structures that are enriched in a dataset relative to comparison data. In a wide variety of experiments, we demonstrate that cPCA with a background dataset enables us to visualize dataset-specific patterns missed by PCA and other standard methods. We further provide a geometric interpretation of cPCA and strong mathematical guarantees. An implementation of cPCA is publicly available, and can be used for exploratory data analysis in many applications where PCA is currently used.

A new scale for disaster nursing core competencies: Development and psychometric testing.

PubMed

Al Thobaity, Abdulellah; Williams, Brett; Plummer, Virginia

2016-02-01

All nurses must have core competencies in preparing for, responding to and recovering from a disaster. In the Kingdom of Saudi Arabia (KSA), as in many other countries, disaster nursing core competencies are not fully understood and lack reliable, validated tools. Thus, it is imperative to develop a scale for exploring disaster nursing core competencies, roles and barriers in the KSA. This study's objective is to develop a valid, reliable scale that identifies and explores core competencies of disaster nursing, nurses' roles in disaster management and barriers to developing disaster nursing in the KSA. This study developed a new scale testing its validity and reliability. A principal component analysis (PCA) was used to develop and test psychometric properties of the new scale. The PCA used a purposive sample of nurses from emergency departments in two hospitals in the KSA. Participants rated 93 paper-based, self-report questionnaire items from 1 to 10 on a Likert scale. PCA using Varimax rotation was conducted to explore factors emerging from responses. The study's participants were 132 nurses (66% response rate). PCA of the 93 questionnaire items revealed 49 redundant items (which were deleted) and 3 factors with eigenvalues of >1. The remaining 44 items accounted for 77.3% of the total variance. The overall Cronbach's alpha was 0.96 for all factors: 0.98 for Factor 1, 0.92 for Factor 2 and 0.86 for Factor 3. This study provided a validated, reliable scale for exploring nurses' core competencies, nurses' roles and barriers to developing disaster nursing in the KSA. The new scale has many implications, such as for improving education, planning and curricula. Crown Copyright © 2015. Published by Elsevier Ltd. All rights reserved.

Feasibility of detecting aflatoxin B1 on inoculated maize kernels surface using Vis/NIR hyperspectral imaging.

PubMed

Wang, Wei; Heitschmidt, Gerald W; Windham, William R; Feldner, Peggy; Ni, Xinzhi; Chu, Xuan

2015-01-01

The feasibility of using a visible/near-infrared hyperspectral imaging system with a wavelength range between 400 and 1000 nm to detect and differentiate different levels of aflatoxin B1 (AFB1 ) artificially titrated on maize kernel surface was examined. To reduce the color effects of maize kernels, image analysis was limited to a subset of original spectra (600 to 1000 nm). Residual staining from the AFB1 on the kernels surface was selected as regions of interest for analysis. Principal components analysis (PCA) was applied to reduce the dimensionality of hyperspectral image data, and then a stepwise factorial discriminant analysis (FDA) was performed on latent PCA variables. The results indicated that discriminant factors F2 can be used to separate control samples from all of the other groups of kernels with AFB1 inoculated, whereas the discriminant factors F1 can be used to identify maize kernels with levels of AFB1 as low as 10 ppb. An overall classification accuracy of 98% was achieved. Finally, the peaks of β coefficients of the discrimination factors F1 and F2 were analyzed and several key wavelengths identified for differentiating maize kernels with and without AFB1 , as well as those with differing levels of AFB1 inoculation. Results indicated that Vis/NIR hyperspectral imaging technology combined with the PCA-FDA was a practical method to detect and differentiate different levels of AFB1 artificially inoculated on the maize kernels surface. However, indicated the potential to detect and differentiate naturally occurring toxins in maize kernel. © 2014 Institute of Food Technologists®

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bednarz, Natalia; Eltze, Elke; Semjonow, Axel

A recent study concluded that serum prostate specific antigen (PSA)-based screening is beneficial for reducing the lethality of PCa, but was also associated with a high risk of 'overdiagnosis'. Nevertheless, also PCa patients who suffered from organ confined tumors and had negative bone scans succumb to distant metastases after complete tumor resection. It is reasonable to assume that those tumors spread to other organs long before the overt manifestation of metastases. Our current results confirm that prostate tumors are highly heterogeneous. Even a small subpopulation of cells bearing BRCA1 losses can initiate PCa cell regional and distant dissemination indicating thosemore » patients which might be at high risk of metastasis. A preliminary study performed on a small cohort of multifocal prostate cancer (PCa) detected BRCA1 allelic imbalances (AI) among circulating tumor cells (CTCs). The present analysis was aimed to elucidate the biological and clinical role of BRCA1 losses on metastatic spread and tumor progression in prostate cancer patients. Experimental Design: To map molecular progression in PCa outgrowth we used FISH analysis of tissue microarrays (TMA), lymph node sections and CTC from peripheral blood. We found that 14% of 133 tested patients carried monoallelic BRCA1 loss in at least one tumor focus. Extended molecular analysis of chr17q revealed that this aberration was often a part of larger cytogenetic rearrangement involving chr17q21 accompanied by AI of the tumor suppressor gene PTEN and lack of the BRCA1 promoter methylation. The BRCA1 losses correlated with advanced T stage (p < 0.05), invasion to pelvic lymph nodes (LN, p < 0.05) as well as BR (p < 0.01). Their prevalence was twice as high within 62 LN metastases (LNMs) as in primary tumors (27%, p < 0.01). The analysis of 11 matched primary PCa-LNM pairs confirmed the suspected transmission of genetic abnormalities between those two sites. In 4 of 7 patients with metastatic disease, BRCA1 losses appeared in a minute fraction of cytokeratin- and vimentin-positive CTCs. Small subpopulations of PCa cells bearing BRCA1 losses might be one confounding factor initiating tumor dissemination and might provide an early indicator of shortened disease-free survival.« less

Motivation for HPV Vaccination Among Young Adult Men: Validation of TTM Decisional Balance and Self-Efficacy Constructs.

PubMed

Fernandez, Anne C; Amoyal, Nicole R; Paiva, Andrea L; Prochaska, James O

2016-01-01

In the United States, 36% of human papillomavirus (HPV)-related cancers occur among men. HPV vaccination can substantially reduce the risk of HPV infection; however, the vast majority of men are unvaccinated. This study developed and validated transtheoretical model-based measures for HPV vaccination in young adult men. Cross-sectional measurement development. Online survey of young adult men. Three hundred twenty-nine mostly college-attending men, ages 18 to 26. Stage of change, decisional balance (pros/cons), and self-efficacy. The sample was randomly split into halves for exploratory principal components analysis (PCA), followed by confirmatory factor analyses (CFA) to test measurement models. Multivariate analyses examined relationships between scales. For decisional balance, PCA revealed two uncorrelated five-item factors (pros α = .78; cons α = .83). For the self-efficacy scale, PCA revealed a single-factor solution (α = .83). CFA confirmed that the two-factor uncorrelated model for decisional balance and a single-factor model for self-efficacy. Follow-up analyses of variance supported the theoretically predicted relationships between stage of change, pros, and self-efficacy. This study resulted in reliable and valid measures of pros and self-efficacy for HPV vaccination that can be used in future clinical research.

Identification of genetic risk associated with prostate cancer using ancestry informative markers

PubMed Central

Ricks-Santi, LJ; Apprey, V; Mason, T; Wilson, B; Abbas, M; Hernandez, W; Hooker, S; Doura, M; Bonney, G; Dunston, G; Kittles, R; Ahaghotu, C

2014-01-01

BACKGROUND Prostate cancer (PCa) is a common malignancy and a leading cause of cancer death among men in the United States with African-American (AA) men having the highest incidence and mortality rates. Given recent results from admixture mapping and genome-wide association studies for PCa in AA men, it is clear that many risk alleles are enriched in men with West African genetic ancestry. METHODS A total of 77 ancestry informative markers (AIMs) within surrounding candidate gene regions were genotyped and haplotyped using Pyrosequencing in 358 unrelated men enrolled in a PCa genetic association study at the Howard University Hospital between 2000 and 2004. Sequence analysis of promoter region single-nucleotide polymorphisms (SNPs) to evaluate disruption of transcription factor-binding sites was conducted using in silico methods. RESULTS Eight AIMs were significantly associated with PCa risk after adjusting for age and West African ancestry. SNP rs1993973 (intervening sequences) had the strongest association with PCa using the log-additive genetic model (P = 0.002). SNPs rs1561131 (genotypic, P = 0.007), rs1963562 (dominant, P = 0.01) and rs615382 (recessive, P = 0.009) remained highly significant after adjusting for both age and ancestry. We also tested the independent effect of each significantly associated SNP and rs1561131 (P = 0.04) and rs1963562 (P = 0.04) remained significantly associated with PCa development. After multiple comparisons testing using the false discovery rate, rs1993973 remained significant. Analysis of the rs156113–, rs1963562–rs615382l and rs1993973–rs585224 haplotypes revealed that the least frequently found haplotypes in this population were significantly associated with a decreased risk of PCa (P = 0.032 and 0.0017, respectively). CONCLUSIONS The approach for SNP selection utilized herein showed that AIMs may not only leverage increased linkage disequilibrium in populations to identify risk and protective alleles, but may also be informative in dissecting the biology of PCa and other health disparities. PMID:22801071

An improved geographically weighted regression model for PM2.5 concentration estimation in large areas

NASA Astrophysics Data System (ADS)

Zhai, Liang; Li, Shuang; Zou, Bin; Sang, Huiyong; Fang, Xin; Xu, Shan

2018-05-01

Considering the spatial non-stationary contributions of environment variables to PM2.5 variations, the geographically weighted regression (GWR) modeling method has been using to estimate PM2.5 concentrations widely. However, most of the GWR models in reported studies so far were established based on the screened predictors through pretreatment correlation analysis, and this process might cause the omissions of factors really driving PM2.5 variations. This study therefore developed a best subsets regression (BSR) enhanced principal component analysis-GWR (PCA-GWR) modeling approach to estimate PM2.5 concentration by fully considering all the potential variables' contributions simultaneously. The performance comparison experiment between PCA-GWR and regular GWR was conducted in the Beijing-Tianjin-Hebei (BTH) region over a one-year-period. Results indicated that the PCA-GWR modeling outperforms the regular GWR modeling with obvious higher model fitting- and cross-validation based adjusted R2 and lower RMSE. Meanwhile, the distribution map of PM2.5 concentration from PCA-GWR modeling also clearly depicts more spatial variation details in contrast to the one from regular GWR modeling. It can be concluded that the BSR enhanced PCA-GWR modeling could be a reliable way for effective air pollution concentration estimation in the coming future by involving all the potential predictor variables' contributions to PM2.5 variations.

A Positive Family History as risk factor for Prostate Cancer in a Population-based Study with organized PSA-Screening: Results of the Swiss ERSPC (Aarau)

PubMed Central

Randazzo, Marco; Müller, Alexander; Carlsson, Sigrid; Eberli, Daniel; Huber, Andreas; Grobholz, Rainer; Manka, Lukas; Mortezavi, Ashkan; Sulser, Tullio; Recker, Franz; Kwiatkowski, Maciej

2016-01-01

Objective To assess the value of positive family history (FH) as a risk factor for prostate cancer (PCa) incidence and grade among men undergoing organized PSA-screening in a population-based study. Patients and Methods The study cohort comprised all attendees of the Swiss arm of the European Randomized Study of Screening for Prostate Cancer (ERSPC) with systematic PSA-tests every 4 years. Men reporting first-degree relative(s) diagnosed with PCa were considered to have a positive FH. Biopsy was exclusively PSA-triggered with a threshold of 3 ng/ml. Primary endpoint was PCa diagnosis. Kaplan-Meier and Cox regression analyses were used. Results Of 4,932 attendees with a median age of 60.9 (IQR 57.6–65.1) years, 334 (6.8%) reported a positive FH. Median follow-up duration was 11.6 years (IQR 10.3–13.3). Cumulative PCa incidence was 60/334 (18%, positive FH) and 550/4,598 (12%, negative FH) (OR 1.6, 95% CI 1.2–2.2, p=0.001), respectively. In both groups, most PCa diagnosed had a low grade. There were no significant differences in PSA at diagnosis, biopsy Gleason score or Gleason score on pathologic specimen among men who underwent radical prostatectomy between both groups, respectively. On multivariable analysis, age (HR 1.04, 95% CI 1.02–1.06), baseline PSA (HR 1.13 95% CI 1.12–1.14), and FH (HR 1.6, CI 1.24–2.14) were independent predictors for overall PCa incidence (p<0.0001 each). Only baseline PSA (HR 1.14, 95% CI 1.12–1.16, p<0.0001) was an independent predictor of Gleason score ≥7 PCa on prostate biopsy. The proportion of interval PCa diagnosed in between the screening rounds was non-significantly different. Conclusion Irrespective of the FH status, the current PSA-based screening setting detects the majority of aggressive PCa and missed only a minority of interval cancers with a 4-year screening algorithm. Our results suggest that men with a positive FH are at increased risk for low grade but not aggressive PCa. PMID:26332304

Consensus statement on definition, diagnosis, and management of high-risk prostate cancer patients on behalf of the Spanish Groups of Uro-Oncology Societies URONCOR, GUO, and SOGUG.

PubMed

Henríquez, I; Rodríguez-Antolín, A; Cassinello, J; Gonzalez San Segundo, C; Unda, M; Gallardo, E; López-Torrecilla, J; Juarez, A; Arranz, J

2018-03-01

Prostate cancer (PCa) is the most prevalent malignancy in men and the second cause of mortality in industrialized countries. Based on Spanish Register of PCa, the incidence of high-risk PCa is 29%, approximately. In spite of the evidence-based beneficial effect of radiotherapy and androgen deprivation therapy in high-risk PCa, these patients (pts) are still a therapeutic challenge for all specialists involved, in part due to the absence of comparative studies to establish which of the present disposable treatments offer better results. Nowadays, high-risk PCa definition is not well consensual through the published oncology guides. Clinical stage, tumour grade, and number of risk factors are relevant to be considered on PCa prognosis. However, these factors are susceptible to change depending on when surgical or radiation therapy is considered to be the treatment of choice. Other factors, such as reference pathologist, different diagnosis biopsy schedules, surgical or radiotherapy techniques, adjuvant treatments, biochemical failures, and follow-up, make it difficult to compare the results between different therapeutic options. This article reviews important issues concerning high-risk PCa. URONCOR, GUO, and SOGUG on behalf of the Spanish Groups of Uro-Oncology Societies have reached a consensus addressing a practical recommendation on definition, diagnosis, and management of high-risk PCa.

Principal component and spatial correlation analysis of spectroscopic-imaging data in scanning probe microscopy.

PubMed

Jesse, Stephen; Kalinin, Sergei V

2009-02-25

An approach for the analysis of multi-dimensional, spectroscopic-imaging data based on principal component analysis (PCA) is explored. PCA selects and ranks relevant response components based on variance within the data. It is shown that for examples with small relative variations between spectra, the first few PCA components closely coincide with results obtained using model fitting, and this is achieved at rates approximately four orders of magnitude faster. For cases with strong response variations, PCA allows an effective approach to rapidly process, de-noise, and compress data. The prospects for PCA combined with correlation function analysis of component maps as a universal tool for data analysis and representation in microscopy are discussed.

Linking Spatial Variations in Water Quality with Water and Land Management using Multivariate Techniques.

PubMed

Wan, Yongshan; Qian, Yun; Migliaccio, Kati White; Li, Yuncong; Conrad, Cecilia

2014-03-01

Most studies using multivariate techniques for pollution source evaluation are conducted in free-flowing rivers with distinct point and nonpoint sources. This study expanded on previous research to a managed "canal" system discharging into the Indian River Lagoon, Florida, where water and land management is the single most important anthropogenic factor influencing water quality. Hydrometric and land use data of four drainage basins were uniquely integrated into the analysis of 25 yr of monthly water quality data collected at seven stations to determine the impact of water and land management on the spatial variability of water quality. Cluster analysis (CA) classified seven monitoring stations into four groups (CA groups). All water quality parameters identified by discriminant analysis showed distinct spatial patterns among the four CA groups. Two-step principal component analysis/factor analysis (PCA/FA) was conducted with (i) water quality data alone and (ii) water quality data in conjunction with rainfall, flow, and land use data. The results indicated that PCA/FA of water quality data alone was unable to identify factors associated with management activities. The addition of hydrometric and land use data into PCA/FA revealed close associations of nutrients and color with land management and storm-water retention in pasture and citrus lands; total suspended solids, turbidity, and NO + NO with flow and Lake Okeechobee releases; specific conductivity with supplemental irrigation supply; and dissolved O with wetland preservation. The practical implication emphasizes the importance of basin-specific land and water management for ongoing pollutant loading reduction and ecosystem restoration programs. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

Coagulation activation by MC28 fibrosarcoma cells facilitates lung tumor formation.

PubMed

Amirkhosravi, M; Francis, J L

1995-01-01

Tumor cells interact with the hemostatic system in various ways and may thus influence malignant growth and spread. MC28 fibrosarcoma cells possess a potent procoagulant activity (PCA) and form lung tumors following intravenous injection. The aim of this work was to study the relationship between PCA, intravascular coagulation and lung seeding in the MC28 model. MC28 cells were injected into control, warfarinized and heparinized hooded Lister rats. Coagulation changes were monitored by thromboelastography (TEG) and Sonoclot analysis (SA), lung fibrin formation by light and electron microscopy, tumor seeding by macroscopic counting and tumor cell and platelet deposition in the lungs by radiolabelling. PCA was measured by chromogenic assay. MC28 PCA was characterized as a tissue factor-factor VIIa complex that probably arose during cell culture or disaggregation of solid tumors. Injection of tumor cells caused marked coagulopathy and was rapidly (within 30 min) followed by fibrin deposition in the lungs and accumulation of radiolabelled platelets. Heparin and warfarin significantly reduced lung seeding (p < 0.001) and reduced retention of radiolabelled tumor cells in the pulmonary circulation (p < 0.01). Inhibition of cellular PCA by prior treatment with concanavalin A markedly reduced intravascular coagulation and lung seeding. We conclude that MC28 cells cause intravascular coagulation as a direct result of their procoagulant activity. The data suggest that tumor cells form complexes with platelets and fibrin which are retained in the lungs long enough for extravasation and seeding to occur.(ABSTRACT TRUNCATED AT 250 WORDS)

Priority of VHS Development Based in Potential Area using Principal Component Analysis

NASA Astrophysics Data System (ADS)

Meirawan, D.; Ana, A.; Saripudin, S.

2018-02-01

The current condition of VHS is still inadequate in quality, quantity and relevance. The purpose of this research is to analyse the development of VHS based on the development of regional potential by using principal component analysis (PCA) in Bandung, Indonesia. This study used descriptive qualitative data analysis using the principle of secondary data reduction component. The method used is Principal Component Analysis (PCA) analysis with Minitab Statistics Software tool. The results of this study indicate the value of the lowest requirement is a priority of the construction of development VHS with a program of majors in accordance with the development of regional potential. Based on the PCA score found that the main priority in the development of VHS in Bandung is in Saguling, which has the lowest PCA value of 416.92 in area 1, Cihampelas with the lowest PCA value in region 2 and Padalarang with the lowest PCA value.

Item response theory and factor analysis as a mean to characterize occurrence of response shift in a longitudinal quality of life study in breast cancer patients

PubMed Central

2014-01-01

Background The occurrence of response shift (RS) in longitudinal health-related quality of life (HRQoL) studies, reflecting patient adaptation to disease, has already been demonstrated. Several methods have been developed to detect the three different types of response shift (RS), i.e. recalibration RS, 2) reprioritization RS, and 3) reconceptualization RS. We investigated two complementary methods that characterize the occurrence of RS: factor analysis, comprising Principal Component Analysis (PCA) and Multiple Correspondence Analysis (MCA), and a method of Item Response Theory (IRT). Methods Breast cancer patients (n = 381) completed the EORTC QLQ-C30 and EORTC QLQ-BR23 questionnaires at baseline, immediately following surgery, and three and six months after surgery, according to the “then-test/post-test” design. Recalibration was explored using MCA and a model of IRT, called the Linear Logistic Model with Relaxed Assumptions (LLRA) using the then-test method. Principal Component Analysis (PCA) was used to explore reconceptualization and reprioritization. Results MCA highlighted the main profiles of recalibration: patients with high HRQoL level report a slightly worse HRQoL level retrospectively and vice versa. The LLRA model indicated a downward or upward recalibration for each dimension. At six months, the recalibration effect was statistically significant for 11/22 dimensions of the QLQ-C30 and BR23 according to the LLRA model (p ≤ 0.001). Regarding the QLQ-C30, PCA indicated a reprioritization of symptom scales and reconceptualization via an increased correlation between functional scales. Conclusions Our findings demonstrate the usefulness of these analyses in characterizing the occurrence of RS. MCA and IRT model had convergent results with then-test method to characterize recalibration component of RS. PCA is an indirect method in investigating the reprioritization and reconceptualization components of RS. PMID:24606836

An Efficient Taguchi Approach for the Performance Optimization of Health, Safety, Environment and Ergonomics in Generation Companies

PubMed Central

Azadeh, Ali; Sheikhalishahi, Mohammad

2014-01-01

Background A unique framework for performance optimization of generation companies (GENCOs) based on health, safety, environment, and ergonomics (HSEE) indicators is presented. Methods To rank this sector of industry, the combination of data envelopment analysis (DEA), principal component analysis (PCA), and Taguchi are used for all branches of GENCOs. These methods are applied in an integrated manner to measure the performance of GENCO. The preferred model between DEA, PCA, and Taguchi is selected based on sensitivity analysis and maximum correlation between rankings. To achieve the stated objectives, noise is introduced into input data. Results The results show that Taguchi outperforms other methods. Moreover, a comprehensive experiment is carried out to identify the most influential factor for ranking GENCOs. Conclusion The approach developed in this study could be used for continuous assessment and improvement of GENCO's performance in supplying energy with respect to HSEE factors. The results of such studies would help managers to have better understanding of weak and strong points in terms of HSEE factors. PMID:26106505

Design of experiments and principal component analysis as approaches for enhancing performance of gas-diffusional air-breathing bilirubin oxidase cathode

NASA Astrophysics Data System (ADS)

Babanova, Sofia; Artyushkova, Kateryna; Ulyanova, Yevgenia; Singhal, Sameer; Atanassov, Plamen

2014-01-01

Two statistical methods, design of experiments (DOE) and principal component analysis (PCA) are employed to investigate and improve performance of air-breathing gas-diffusional enzymatic electrodes. DOE is utilized as a tool for systematic organization and evaluation of various factors affecting the performance of the composite system. Based on the results from the DOE, an improved cathode is constructed. The current density generated utilizing the improved cathode (755 ± 39 μA cm-2 at 0.3 V vs. Ag/AgCl) is 2-5 times higher than the highest current density previously achieved. Three major factors contributing to the cathode performance are identified: the amount of enzyme, the volume of phosphate buffer used to immobilize the enzyme, and the thickness of the gas-diffusion layer (GDL). PCA is applied as an independent confirmation tool to support conclusions made by DOE and to visualize the contribution of factors in individual cathode configurations.

Beneficial effects of the naturally occurring flavonoid silibinin on the prostate cancer microenvironment: role of monocyte chemotactic protein-1 and immune cell recruitment.

PubMed

Ting, Harold; Deep, Gagan; Kumar, Sushil; Jain, Anil K; Agarwal, Chapla; Agarwal, Rajesh

2016-06-01

Tumor microenvironment plays an essential role in prostate carcinogenesis and offers novel opportunities to prevent and treat prostate cancer (PCA). Here, we investigated the ability of cancer-associated fibroblasts (CAFs) to promote PCA progression, and silibinin efficacy to target this response. We collected conditioned media from CAFs treated with vehicle or silibinin, and labeled as control conditioned media (CCM) or silibinin-treatment conditioned media (SBCM), respectively. Next, we characterized the effect of CCM and SBCM treatment in several PCA cell lines (RWPE-1, WPE-1 NA-22, WPE-1 NB-14 and PC3). Result showed that compared with SBCM, CCM significantly reduces E-cadherin expression and increases invasiveness and clonogenicity in PCA cells. Further molecular studies identified monocyte chemotactic protein-1 (MCP-1) as the key component of CCM that promotes PCA invasiveness, whereas silibinin treatment strongly reduced MCP-1 expression in CAFs by inhibiting the DNA-binding activity of MCP-1 transcriptional regulators-nuclear factor-kappaB and AP-1. In vivo, silibinin feeding (200mg/kg body weight) strongly reduced TRAMPC1 allografts growth (by 68%) in syngeneic C57Bl/6 mice. TRAMPC1 tumor analysis showed that silibinin reduced MCP-1 and CAFs' biomarkers (fibroblast activation protein, α-smooth muscle actin, transforming growth factor beta 2, vimentin etc.) and significantly modulated the recruitment of immune cells in the tumor microenvironment. Similar inhibitory effects of silibinin on MCP-1 and immune cells recruitment were also observed in TRAMP PCA tissues with reported silibinin efficacy. Overall, our data suggest that silibinin can target CAF-mediated invasiveness in PCA by inhibiting MCP-1 secretion. This, in turn, was associated with a reduction in immune cell recruitment in vivo along with a marked reduction in tumor growth. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Beneficial effects of the naturally occurring flavonoid silibinin on the prostate cancer microenvironment: role of monocyte chemotactic protein-1 and immune cell recruitment

PubMed Central

Ting, Harold; Deep, Gagan; Kumar, Sushil; Jain, Anil K.; Agarwal, Chapla; Agarwal, Rajesh

2016-01-01

Tumor microenvironment plays an essential role in prostate carcinogenesis and offers novel opportunities to prevent and treat prostate cancer (PCA). Here, we investigated the ability of cancer-associated fibroblasts (CAFs) to promote PCA progression, and silibinin efficacy to target this response. We collected conditioned media from CAFs treated with vehicle or silibinin, and labeled as control conditioned media (CCM) or silibinin-treatment conditioned media (SBCM), respectively. Next, we characterized the effect of CCM and SBCM treatment in several PCA cell lines (RWPE-1, WPE-1 NA-22, WPE-1 NB-14 and PC3). Result showed that compared with SBCM, CCM significantly reduces E-cadherin expression and increases invasiveness and clonogenicity in PCA cells. Further molecular studies identified monocyte chemotactic protein-1 (MCP-1) as the key component of CCM that promotes PCA invasiveness, whereas silibinin treatment strongly reduced MCP-1 expression in CAFs by inhibiting the DNA-binding activity of MCP-1 transcriptional regulators—nuclear factor-kappaB and AP-1. In vivo, silibinin feeding (200mg/kg body weight) strongly reduced TRAMPC1 allografts growth (by 68%) in syngeneic C57Bl/6 mice. TRAMPC1 tumor analysis showed that silibinin reduced MCP-1 and CAFs’ biomarkers (fibroblast activation protein, α-smooth muscle actin, transforming growth factor beta 2, vimentin etc.) and significantly modulated the recruitment of immune cells in the tumor microenvironment. Similar inhibitory effects of silibinin on MCP-1 and immune cells recruitment were also observed in TRAMP PCA tissues with reported silibinin efficacy. Overall, our data suggest that silibinin can target CAF-mediated invasiveness in PCA by inhibiting MCP-1 secretion. This, in turn, was associated with a reduction in immune cell recruitment in vivo along with a marked reduction in tumor growth. PMID:27207648

Apparent diffusion coefficients in prostate cancer: correlation with molecular markers Ki-67, HIF-1α and VEGF.

PubMed

Ma, Teng; Yang, Shaolin; Jing, Haiyan; Cong, Lin; Cao, Zhixin; Liu, Zhiling; Huang, Zhaoqin

2018-03-01

Prostate cancer (PCa) is the second most common cancer in men. The Gleason score (GS) and biomarkers play important roles in the diagnosis and treatment of patients with PCa. The purpose of this study was to investigate the relationship between the apparent diffusion coefficient (ADC) and the molecular markers Ki-67, hypoxia-inducible factor-1α (HIF-1α) and vascular endothelial growth factor (VEGF) in PCa. Thirty-nine patients with 39 lesions, who had been diagnosed with PCa, were enrolled in this study. All patients underwent diffusion-weighted magnetic resonance imaging (DW-MRI) (b = 800 s/mm 2 ). The expression of Ki-67, HIF-1α and VEGF was assessed by immunohistochemistry. Statistical analysis was applied to analyze the association between ADC and prostate-specific antigen (PSA), GS and the expression of Ki-67, HIF-1α and VEGF. The group differences in ADC among different grades of Ki-67, HIF-1α and VEGF were also analyzed. The mean ± standard deviation of ADC was (0.76 ± 0.27) × 10 -3  mm 2 /s. ADC correlated negatively with PSA and GS (p < 0.05). The Ki-67 staining index (SI), HIF-1α expression and VEGF expression in PCa were correlated inversely with ADC, controlling for age (r = -0.332, p < 0.05; r = -0.662, p < 0.0005; and r = -0.714, p < 0.0005, respectively). ADC showed a significant difference among different grades of Ki-67 (F = 9.164, p = 0.005), HIF-1α (F = 40.333, p < 0.0005) and VEGF (F = 22.048, p < 0.0005). In conclusion, ADC was correlated with PSA, GS, and Ki-67, HIF-1α and VEGF expression in patients with PCa. ADC may be used to evaluate tumor proliferation, hypoxia and angiogenesis in PCa. Copyright © 2018 John Wiley & Sons, Ltd.

A propensity score approach to correction for bias due to population stratification using genetic and non-genetic factors.

PubMed

Zhao, Huaqing; Rebbeck, Timothy R; Mitra, Nandita

2009-12-01

Confounding due to population stratification (PS) arises when differences in both allele and disease frequencies exist in a population of mixed racial/ethnic subpopulations. Genomic control, structured association, principal components analysis (PCA), and multidimensional scaling (MDS) approaches have been proposed to address this bias using genetic markers. However, confounding due to PS can also be due to non-genetic factors. Propensity scores are widely used to address confounding in observational studies but have not been adapted to deal with PS in genetic association studies. We propose a genomic propensity score (GPS) approach to correct for bias due to PS that considers both genetic and non-genetic factors. We compare the GPS method with PCA and MDS using simulation studies. Our results show that GPS can adequately adjust and consistently correct for bias due to PS. Under no/mild, moderate, and severe PS, GPS yielded estimated with bias close to 0 (mean=-0.0044, standard error=0.0087). Under moderate or severe PS, the GPS method consistently outperforms the PCA method in terms of bias, coverage probability (CP), and type I error. Under moderate PS, the GPS method consistently outperforms the MDS method in terms of CP. PCA maintains relatively high power compared to both MDS and GPS methods under the simulated situations. GPS and MDS are comparable in terms of statistical properties such as bias, type I error, and power. The GPS method provides a novel and robust tool for obtaining less-biased estimates of genetic associations that can consider both genetic and non-genetic factors. 2009 Wiley-Liss, Inc.

Comparison of 3 Methods for Identifying Dietary Patterns Associated With Risk of Disease

PubMed Central

DiBello, Julia R.; Kraft, Peter; McGarvey, Stephen T.; Goldberg, Robert; Campos, Hannia

2008-01-01

Reduced rank regression and partial least-squares regression (PLS) are proposed alternatives to principal component analysis (PCA). Using all 3 methods, the authors derived dietary patterns in Costa Rican data collected on 3,574 cases and controls in 1994–2004 and related the resulting patterns to risk of first incident myocardial infarction. Four dietary patterns associated with myocardial infarction were identified. Factor 1, characterized by high intakes of lean chicken, vegetables, fruit, and polyunsaturated oil, was generated by all 3 dietary pattern methods and was associated with a significantly decreased adjusted risk of myocardial infarction (28%–46%, depending on the method used). PCA and PLS also each yielded a pattern associated with a significantly decreased risk of myocardial infarction (31% and 23%, respectively); this pattern was characterized by moderate intake of alcohol and polyunsaturated oil and low intake of high-fat dairy products. The fourth factor derived from PCA was significantly associated with a 38% increased risk of myocardial infarction and was characterized by high intakes of coffee and palm oil. Contrary to previous studies, the authors found PCA and PLS to produce more patterns associated with cardiovascular disease than reduced rank regression. The most effective method for deriving dietary patterns related to disease may vary depending on the study goals. PMID:18945692

Risk of prostate cancer in African-American men: Evidence of mixed effects of dietary quercetin by serum vitamin D status.

PubMed

Paller, C J; Kanaan, Y M; Beyene, D A; Naab, T J; Copeland, R L; Tsai, H L; Kanarek, N F; Hudson, T S

2015-09-01

African-American (AA) men experience higher rates of prostate cancer (PCa) and vitamin D (vitD) deficiency than white men. VitD is promoted for PCa prevention, but there is conflicting data on the association between vitD and PCa. We examined the association between serum vitD and dietary quercetin and their interaction with PCa risk in AA men. Participants included 90 AA men with PCa undergoing treatment at Howard University Hospital (HUH) and 62 controls participating in HUH's free PCa screening program. We measured serum 25-hydroxy vitD [25(OH)D] and used the 98.2 item Block Brief 2000 Food Frequency Questionnaires to measure dietary intake of quercetin and other nutrients. Case and control groups were compared using a two-sample t-test for continuous risk factors and a Fisher exact test for categorical factors. Associations between risk factors and PCa risk were examined via age-adjusted logistic regression models. Interaction effects of dietary quercetin and serum vitD on PCa status were observed. AA men (age 40-70) with normal levels of serum vitD (>30 ng/ml) had a 71% lower risk of PCa compared to AA men with vitD deficiency (OR = 0.29, 95%CI: 0.08-1.03; P = 0.055). In individuals with vitD deficiency, increased dietary quercetin showed a tendency toward lower risk of PCa (OR = 0.91, 95%CI: 0.82-1.00; P = 0.054, age-adjusted) while men with normal vitD were at elevated risk (OR = 1.23, 95%CI: 1.04-1.45). These findings suggest that AA men who are at a higher risk of PCa may benefit more from vitD intake, and supplementation with dietary quercetin may increase the risk of PCa in AA men with normal vitD levels. Further studies with larger populations are needed to better understand the impact of the interaction between sera vitD levels and supplementation with quercetin on PCa in AA men. © 2015 Wiley Periodicals, Inc.

[Habitat factor analysis for Torreya grandis cv. Merrillii based on spatial information technology].

PubMed

Wang, Xiao-ming; Wang, Ke; Ao, Wei-jiu; Deng, Jin-song; Han, Ning; Zhu, Xiao-yun

2008-11-01

Torreya grandis cv. Merrillii, a tertiary survival plant, is a rare tree species of significant economic value and expands rapidly in China. Its special habitat factor analysis has the potential value to provide guide information for its planting, management, and sustainable development, because the suitable growth conditions for this tree species are special and strict. In this paper, the special habitat factors for T. grandis cv. Merrillii in its core region, i.e., in seven villages of Zhuji City, Zhejiang Province were analyzed with Principal Component Analysis (PCA) and a series of data, such as IKONOS image, Digital Elevation Model (DEM), and field survey data supported by the spatial information technology. The results showed that T. grandis cv. Merrillii exhibited high selectivity of environmental factors such as elevation, slope, and aspect. 96.22% of T. grandis cv. Merrillii trees were located at the elevation from 300 to 600 m, 97.52% of them were found to present on the areas whose slope was less than 300, and 74.43% of them distributed on sunny and half-sunny slopes. The results of PCA analysis indicated that the main environmental factors affecting the habitat of T. grandis cv. Merrillii were moisture, heat, and soil nutrients, and moisture might be one of the most important ecological factors for T. grandis cv. Merrillii due to the unique biological and ecological characteristics of the tree species.

Non-fluent speech following stroke is caused by impaired efference copy.

PubMed

Feenaughty, Lynda; Basilakos, Alexandra; Bonilha, Leonardo; den Ouden, Dirk-Bart; Rorden, Chris; Stark, Brielle; Fridriksson, Julius

2017-09-01

Efference copy is a cognitive mechanism argued to be critical for initiating and monitoring speech: however, the extent to which breakdown of efference copy mechanisms impact speech production is unclear. This study examined the best mechanistic predictors of non-fluent speech among 88 stroke survivors. Objective speech fluency measures were subjected to a principal component analysis (PCA). The primary PCA factor was then entered into a multiple stepwise linear regression analysis as the dependent variable, with a set of independent mechanistic variables. Participants' ability to mimic audio-visual speech ("speech entrainment response") was the best independent predictor of non-fluent speech. We suggest that this "speech entrainment" factor reflects integrity of internal monitoring (i.e., efference copy) of speech production, which affects speech initiation and maintenance. Results support models of normal speech production and suggest that therapy focused on speech initiation and maintenance may improve speech fluency for individuals with chronic non-fluent aphasia post stroke.

Quality of life in Essential Tremor Questionnaire (QUEST): development and initial validation.

PubMed

Tröster, Alexander I; Pahwa, Rajesh; Fields, Julie A; Tanner, Caroline M; Lyons, Kelly E

2005-09-01

Essential tremor (ET) can diminish functioning and quality of life (QOL) but generic QOL measures may be relatively insensitive to ET and its therapies. We sought to develop an ET-specific measure that might be more sensitive, acceptable to patients, relatively brief, and easily used. A sample of 200 patients (average age 70 years, range 30-91; average disease duration 15 years) rated the extent to which tremor impacts a function or state, tremor severity in various body parts, perceived health, and overall QOL. Responses to this initial questionnaire were subjected to principal components analysis (PCA). Inspection of factor coordinates, Eigenvalues, variance accounted for, and correlation matrices were used to select items for confirmatory PCA. Final scale reliability was assessed using Cronbach's alpha. Validity was evaluated by correlations between QOL scales and self-rated tremor severity. PCA of 65 initial items yielded 11 factors accounting for 71% of variance. Six factors were discarded. Two items were eliminated for not loading on a factor and 33 for perceived redundancy. Confirmatory PCA of the retained 30 items yielded an almost identical factor structure (six factors, 70% of variance accounted for, and similar item loadings). Because two factors had very few items loading on them, these two factors were combined into one scale. The final measure has five scales: Physical, Psychosocial, Communication, Hobbies/Leisure, and Work/Finance. Reliability was excellent for the whole instrument and four scales (> or =0.89), and good for the Work/Finance scale (0.79). Severity of voice and head tremor were the best correlates of Communication (0.70 and 0.35), while the Physical scale was related to right and left upper extremity tremor (0.59 and 0.56). Scales correlated more highly with patients' rating of their overall QOL than their health perception. A brief, 30-item, ET-specific QOL scale with excellent reliability was developed. Preliminary validity data are encouraging. The Quality of Life in Essential Tremor Questionnaire (QUEST) promises to facilitate QOL measurement in ET.

Research on distributed heterogeneous data PCA algorithm based on cloud platform

NASA Astrophysics Data System (ADS)

Zhang, Jin; Huang, Gang

2018-05-01

Principal component analysis (PCA) of heterogeneous data sets can solve the problem that centralized data scalability is limited. In order to reduce the generation of intermediate data and error components of distributed heterogeneous data sets, a principal component analysis algorithm based on heterogeneous data sets under cloud platform is proposed. The algorithm performs eigenvalue processing by using Householder tridiagonalization and QR factorization to calculate the error component of the heterogeneous database associated with the public key to obtain the intermediate data set and the lost information. Experiments on distributed DBM heterogeneous datasets show that the model method has the feasibility and reliability in terms of execution time and accuracy.

Probing long-range interactions by extracting free energies from genome-wide chromosome conformation capture data.

PubMed

Saberi, Saeed; Farré, Pau; Cuvier, Olivier; Emberly, Eldon

2015-05-23

A variety of DNA binding proteins are involved in regulating and shaping the packing of chromatin. They aid the formation of loops in the DNA that function to isolate different structural domains. A recent experimental technique, Hi-C, provides a method for determining the frequency of such looping between all distant parts of the genome. Given that the binding locations of many chromatin associated proteins have also been measured, it has been possible to make estimates for their influence on the long-range interactions as measured by Hi-C. However, a challenge in this analysis is the predominance of non-specific contacts that mask out the specific interactions of interest. We show that transforming the Hi-C contact frequencies into free energies gives a natural method for separating out the distance dependent non-specific interactions. In particular we apply Principal Component Analysis (PCA) to the transformed free energy matrix to identify the dominant modes of interaction. PCA identifies systematic effects as well as high frequency spatial noise in the Hi-C data which can be filtered out. Thus it can be used as a data driven approach for normalizing Hi-C data. We assess this PCA based normalization approach, along with several other normalization schemes, by fitting the transformed Hi-C data using a pairwise interaction model that takes as input the known locations of bound chromatin factors. The result of fitting is a set of predictions for the coupling energies between the various chromatin factors and their effect on the energetics of looping. We show that the quality of the fit can be used as a means to determine how much PCA filtering should be applied to the Hi-C data. We find that the different normalizations of the Hi-C data vary in the quality of fit to the pairwise interaction model. PCA filtering can improve the fit, and the predicted coupling energies lead to biologically meaningful insights for how various chromatin bound factors influence the stability of DNA loops in chromatin.

Comparison of prostate cancer gene 3 score, prostate health index and percentage free prostate-specific antigen for differentiating histological inflammation from prostate cancer and other non-neoplastic alterations of the prostate at initial biopsy.

PubMed

De Luca, Stefano; Passera, Roberto; Bollito, Enrico; Manfredi, Matteo; Scarpa, Roberto Mario; Sottile, Antonino; Randone, Donato Franco; Porpiglia, Francesco

2014-12-01

To determine if prostate cancer gene 3 (PCA3) score, Prostate Health Index (PHI), and percent free prostate-specific antigen (%fPSA) may be used to differentiate prostatitis from prostate cancer (PCa), benign prostatic hyperplasia (BPH) and high-grade prostate intraepithelial neoplasia (HG-PIN) in patients with elevated PSA and negative digital rectal examination (DRE). in the present prospective study, 274 patients, undergoing PCA3 score, PHI and %fPSA assessments before initial biopsy, were enrolled. Three multivariate logistic regression models were used to test PCA3 score, PHI and %fPSA as risk factors for prostatitis vs. PCa, vs. BPH, and vs. HG-PIN. All the analyses were performed for the whole patient cohort and for the 'gray zone' of PSA (4-10 ng/ml) cohort (188 individuals). The determinants for prostatitis vs. PCa were PCA3 score, PHI and %fPSA (Odds Ratio [OR]=0.97, 0.96 and 0.94, respectively). Unit increase of PHI was the only risk factor for prostatitis vs. BPH (OR=1.06), and unit increase of PCA3 score for HG-PIN vs. prostatitis (OR=0.98). In the 'gray zone' PSA cohort, the determinants for prostatitis vs. PCa were PCA3 score, PHI and %fPSA (OR=0.96, 0.94 and 0.92, respectively), PCA3 score and PHI for prostatitis vs. BPH (OR=0.96 and 1.08, respectively), and PCA3 score for prostatitis vs. HG-PIN (OR=0.97). The clinical benefit of using PCA3 score and PHI to estimate prostatitis vs. PCa was comparable; even %fPSA had good diagnostic performance, being a faster and cheaper marker. PHI was the only determinant for prostatitis vs. BPH, while PCA3 score for prostatitis vs. HG-PIN. Copyright© 2014 International Institute of Anticancer Research (Dr. John G. Delinassios), All rights reserved.

Method for factor analysis of GC/MS data

DOEpatents

Van Benthem, Mark H; Kotula, Paul G; Keenan, Michael R

2012-09-11

The method of the present invention provides a fast, robust, and automated multivariate statistical analysis of gas chromatography/mass spectroscopy (GC/MS) data sets. The method can involve systematic elimination of undesired, saturated peak masses to yield data that follow a linear, additive model. The cleaned data can then be subjected to a combination of PCA and orthogonal factor rotation followed by refinement with MCR-ALS to yield highly interpretable results.

Behavior of the PCA3 gene in the urine of men with high grade prostatic intraepithelial neoplasia.

PubMed

Morote, Juan; Rigau, Marina; Garcia, Marta; Mir, Carmen; Ballesteros, Carlos; Planas, Jacques; Raventós, Carles X; Placer, José; de Torres, Inés M; Reventós, Jaume; Doll, Andreas

2010-12-01

An ideal marker for the early detection of prostate cancer (PCa) should also differentiate between men with isolated high grade prostatic intraepithelial neoplasia (HGPIN) and those with PCa. Prostate Cancer Gene 3 (PCA3) is a highly specific PCa gene and its score, in relation to the PSA gene in post-prostate massage urine (PMU-PCA3), seems to be useful in ruling out PCa, especially after a negative prostate biopsy. Because PCA3 is also expressed in the HGPIN lesion, the aim of this study was to determine the efficacy of PMU-PCA3 scores for ruling out PCa in men with previous HGPIN. The PMU-PCA3 score was assessed by quantitative PCR (multiplex research assay) in 244 men subjected to prostate biopsy: 64 men with an isolated HGPIN (no cancer detected after two or more repeated biopsies), 83 men with PCa and 97 men with benign pathology findings (BP: no PCa, HGPIN or ASAP). The median PMU-PCA3 score was 1.56 in men with BP, 2.01 in men with HGPIN (p = 0.128) and 9.06 in men with PCa (p = 0.008). The AUC in the ROC analysis was 0.705 in the subset of men with BP and PCa, while it decreased to 0.629 when only men with isolated HGPIN and PCa were included in the analysis. Fixing the sensitivity of the PMU-PCA3 score at 90%, its specificity was 79% in men with BP and 69% in men with isolated HGPIN. The efficacy of the PMU-PCA3 score to rule out PCa in men with HGPIN is lower than in men with BP.

Analysis of the principal component algorithm in phase-shifting interferometry.

PubMed

Vargas, J; Quiroga, J Antonio; Belenguer, T

2011-06-15

We recently presented a new asynchronous demodulation method for phase-sampling interferometry. The method is based in the principal component analysis (PCA) technique. In the former work, the PCA method was derived heuristically. In this work, we present an in-depth analysis of the PCA demodulation method.

Proportion and characteristics of men with unknown risk category in the National Prostate Cancer Register of Sweden.

PubMed

Tomic, Katarina; Westerberg, Marcus; Robinson, David; Garmo, Hans; Stattin, Pär

2016-12-01

Knowledge on missing data in a clinical cancer register is important to assess the validity of research results. For analysis of prostate cancer (Pca), risk category, a composite variable based on serum levels of prostate specific antigen (PSA), stage, and Gleason score, is crucial for treatment decisions and a strong determinant of outcome. The aim of this study was to assess the proportion and characteristics of men in the National Prostate Cancer Register (NPCR) of Sweden with unknown risk category. Men diagnosed with Pca between 1998 and 2012 registered in NPCR with known or unknown risk category were compared with respect to age, socioeconomic factors, comorbidity, cancer characteristics, cancer treatment, and mortality from Pca and other causes. In total, 3315 of 129 391 (3%) men had unknown risk category. Compared to other men in NPCR, these men more often had a concomitant bladder cancer diagnosis, 19% versus 1%, diagnosis of benign prostatic hyperplasia 31% versus 5%, received unspecified Pca treatment 16% versus 3%, had higher comorbidity, Charlson Comorbidity Index 2 or higher, 34% versus 13%, and had lower Pca mortality 12% versus 30%, but similar mortality from other causes. Men with unknown risk category were rare in NPCR but distinctly different from other men in NPCR in many aspects including higher comorbidity and lower Pca mortality.

Fluorescence, electrophoretic and chromatographic fingerprints of herbal medicines and their comparative chemometric analysis.

PubMed

Mazina, Jekaterina; Vaher, Merike; Kuhtinskaja, Maria; Poryvkina, Larisa; Kaljurand, Mihkel

2015-07-01

The aim of the present study was to compare the polyphenolic compositions of 47 medicinal herbs (HM) and four herbal tea mixtures from Central Estonia by rapid, reliable and sensitive Spectral Fluorescence Signature (SFS) method in a front face mode. The SFS method was validated for the main identified HM representatives including detection limits (0.037mgL(-1) for catechin, 0.052mgL(-1) for protocatechuic acid, 0.136mgL(-1) for chlorogenic acid, 0.058mgL(-1) for syringic acid and 0.256mgL(-1) for ferulic acid), linearity (up to 5.0-15mgL(-1)), intra-day precision (RSDs=6.6-10.6%), inter-day precision (RSDs=6.4-13.8%), matrix effect (-15.8 to +5.5) and recovery (85-107%). The phytochemical fingerprints were differentiated by parallel factor analysis (PARAFAC) combined with hierarchical cluster analysis (CA) and principal component analysis (PCA). HM were clustered into four main clusters (catechin-like, hydroxycinnamic acid-like, dihydrobenzoic acid-like derivatives containing HM and HM with low/very low content of fluorescent constituents) and 14 subclusters (rich, medium, low/very low contents). The average accuracy and precision of CA for validation HM set were 97.4% (within 85.2-100%) and 89.6%, (within 66.7-100%), respectively. PARAFAC-PCA/CA has improved the analysis of HM by the SFS method. The results were verified by two separation methods CE-DAD and HPLC-DAD-MS also combined with PARAFAC-PCA/CA. The SFS-PARAFAC-PCA/CA method has potential as a rapid and reliable tool for investigating the fingerprints and predicting the composition of HM or evaluating the quality and authenticity of different standardised formulas. Moreover, SFS-PARAFAC-PCA/CA can be implemented as a laboratory and/or an onsite method. Copyright © 2015 Elsevier B.V. All rights reserved.

Germline BRCA mutations are associated with higher risk of nodal involvement, distant metastasis, and poor survival outcomes in prostate cancer.

PubMed

Castro, Elena; Goh, Chee; Olmos, David; Saunders, Ed; Leongamornlert, Daniel; Tymrakiewicz, Malgorzata; Mahmud, Nadiya; Dadaev, Tokhir; Govindasami, Koveela; Guy, Michelle; Sawyer, Emma; Wilkinson, Rosemary; Ardern-Jones, Audrey; Ellis, Steve; Frost, Debra; Peock, Susan; Evans, D Gareth; Tischkowitz, Marc; Cole, Trevor; Davidson, Rosemarie; Eccles, Diana; Brewer, Carole; Douglas, Fiona; Porteous, Mary E; Donaldson, Alan; Dorkins, Huw; Izatt, Louise; Cook, Jackie; Hodgson, Shirley; Kennedy, M John; Side, Lucy E; Eason, Jacqueline; Murray, Alex; Antoniou, Antonis C; Easton, Douglas F; Kote-Jarai, Zsofia; Eeles, Rosalind

2013-05-10

To analyze the baseline clinicopathologic characteristics of prostate tumors with germline BRCA1 and BRCA2 (BRCA1/2) mutations and the prognostic value of those mutations on prostate cancer (PCa) outcomes. This study analyzed the tumor features and outcomes of 2,019 patients with PCa (18 BRCA1 carriers, 61 BRCA2 carriers, and 1,940 noncarriers). The Kaplan-Meier method and Cox regression analysis were used to evaluate the associations between BRCA1/2 status and other PCa prognostic factors with overall survival (OS), cause-specific OS (CSS), CSS in localized PCa (CSS_M0), metastasis-free survival (MFS), and CSS from metastasis (CSS_M1). PCa with germline BRCA1/2 mutations were more frequently associated with Gleason ≥ 8 (P = .00003), T3/T4 stage (P = .003), nodal involvement (P = .00005), and metastases at diagnosis (P = .005) than PCa in noncarriers. CSS was significantly longer in noncarriers than in carriers (15.7 v 8.6 years, multivariable analyses [MVA] P = .015; hazard ratio [HR] = 1.8). For localized PCa, 5-year CSS and MFS were significantly higher in noncarriers (96% v 82%; MVA P = .01; HR = 2.6%; and 93% v 77%; MVA P = .009; HR = 2.7, respectively). Subgroup analyses confirmed the poor outcomes in BRCA2 patients, whereas the role of BRCA1 was not well defined due to the limited size and follow-up in this subgroup. Our results confirm that BRCA1/2 mutations confer a more aggressive PCa phenotype with a higher probability of nodal involvement and distant metastasis. BRCA mutations are associated with poor survival outcomes and this should be considered for tailoring clinical management of these patients.

Germline BRCA Mutations Are Associated With Higher Risk of Nodal Involvement, Distant Metastasis, and Poor Survival Outcomes in Prostate Cancer

PubMed Central

Castro, Elena; Goh, Chee; Olmos, David; Saunders, Ed; Leongamornlert, Daniel; Tymrakiewicz, Malgorzata; Mahmud, Nadiya; Dadaev, Tokhir; Govindasami, Koveela; Guy, Michelle; Sawyer, Emma; Wilkinson, Rosemary; Ardern-Jones, Audrey; Ellis, Steve; Frost, Debra; Peock, Susan; Evans, D. Gareth; Tischkowitz, Marc; Cole, Trevor; Davidson, Rosemarie; Eccles, Diana; Brewer, Carole; Douglas, Fiona; Porteous, Mary E.; Donaldson, Alan; Dorkins, Huw; Izatt, Louise; Cook, Jackie; Hodgson, Shirley; Kennedy, M. John; Side, Lucy E.; Eason, Jacqueline; Murray, Alex; Antoniou, Antonis C.; Easton, Douglas F.; Kote-Jarai, Zsofia; Eeles, Rosalind

2013-01-01

Purpose To analyze the baseline clinicopathologic characteristics of prostate tumors with germline BRCA1 and BRCA2 (BRCA1/2) mutations and the prognostic value of those mutations on prostate cancer (PCa) outcomes. Patients and Methods This study analyzed the tumor features and outcomes of 2,019 patients with PCa (18 BRCA1 carriers, 61 BRCA2 carriers, and 1,940 noncarriers). The Kaplan-Meier method and Cox regression analysis were used to evaluate the associations between BRCA1/2 status and other PCa prognostic factors with overall survival (OS), cause-specific OS (CSS), CSS in localized PCa (CSS_M0), metastasis-free survival (MFS), and CSS from metastasis (CSS_M1). Results PCa with germline BRCA1/2 mutations were more frequently associated with Gleason ≥ 8 (P = .00003), T3/T4 stage (P = .003), nodal involvement (P = .00005), and metastases at diagnosis (P = .005) than PCa in noncarriers. CSS was significantly longer in noncarriers than in carriers (15.7 v 8.6 years, multivariable analyses [MVA] P = .015; hazard ratio [HR] = 1.8). For localized PCa, 5-year CSS and MFS were significantly higher in noncarriers (96% v 82%; MVA P = .01; HR = 2.6%; and 93% v 77%; MVA P = .009; HR = 2.7, respectively). Subgroup analyses confirmed the poor outcomes in BRCA2 patients, whereas the role of BRCA1 was not well defined due to the limited size and follow-up in this subgroup. Conclusion Our results confirm that BRCA1/2 mutations confer a more aggressive PCa phenotype with a higher probability of nodal involvement and distant metastasis. BRCA mutations are associated with poor survival outcomes and this should be considered for tailoring clinical management of these patients. PMID:23569316

PSMA redirects cell survival signaling from the MAPK to the PI3K-AKT pathways to promote the progression of prostate cancer

PubMed Central

Caromile, Leslie Ann; Dortche, Kristina; Rahman, M. Mamunur; Grant, Christina L.; Stoddard, Christopher; Ferrer, Fernando A.; Shapiro, Linda H.

2017-01-01

Increased abundance of the prostate-specific membrane antigen (PSMA) on prostate epithelium is a hallmark of advanced metastatic prostate cancer (PCa) and correlates negatively with prognosis. However, direct evidence that PSMA functionally contributes to PCa progression remains elusive. We generated mice bearing PSMA-positive or PSMA-negative PCa by crossing PSMA-deficient mice with transgenic PCa (TRAMP) models, enabling direct assessment of PCa incidence and progression in the presence or absence of PSMA. Compared with PSMA-positive tumors, PSMA-negative tumors were smaller, lower-grade, and more apoptotic with fewer blood vessels, consistent with the recognized proangiogenic function of PSMA. Relative to PSMA-positive tumors, tumors lacking PSMA had less than half the abundance of type 1 insulin-like growth factor receptor (IGF-1R), less activity in the survival pathway mediated by PI3K-AKT signaling, and more activity in the proliferative pathway mediated by MAPK-ERK1/2 signaling. Biochemically, PSMA interacted with the scaffolding protein RACK1, disrupting signaling between the β1 integrin and IGF-1R complex to the MAPK pathway, enabling activation of the AKT pathway instead. Manipulation of PSMA abundance in PCa cell lines recapitulated this signaling pathway switch. Analysis of published databases indicated that IGF-1R abundance, cell proliferation, and expression of transcripts for antiapoptotic markers positively correlated with PSMA abundance in patients, suggesting that this switch may be relevant to human PCa. Our findings suggest that increase in PSMA in prostate tumors contributes to progression by altering normal signal transduction pathways to drive PCa progression and that enhanced signaling through the IGF-1R/β1 integrin axis may occur in other tumors. PMID:28292957

Strain Transient Detection Techniques: A Comparison of Source Parameter Inversions of Signals Isolated through Principal Component Analysis (PCA), Non-Linear PCA, and Rotated PCA

NASA Astrophysics Data System (ADS)

Lipovsky, B.; Funning, G. J.

2009-12-01

We compare several techniques for the analysis of geodetic time series with the ultimate aim to characterize the physical processes which are represented therein. We compare three methods for the analysis of these data: Principal Component Analysis (PCA), Non-Linear PCA (NLPCA), and Rotated PCA (RPCA). We evaluate each method by its ability to isolate signals which may be any combination of low amplitude (near noise level), temporally transient, unaccompanied by seismic emissions, and small scale with respect to the spatial domain. PCA is a powerful tool for extracting structure from large datasets which is traditionally realized through either the solution of an eigenvalue problem or through iterative methods. PCA is an transformation of the coordinate system of our data such that the new "principal" data axes retain maximal variance and minimal reconstruction error (Pearson, 1901; Hotelling, 1933). RPCA is achieved by an orthogonal transformation of the principal axes determined in PCA. In the analysis of meteorological data sets, RPCA has been seen to overcome domain shape dependencies, correct for sampling errors, and to determine principal axes which more closely represent physical processes (e.g., Richman, 1986). NLPCA generalizes PCA such that principal axes are replaced by principal curves (e.g., Hsieh 2004). We achieve NLPCA through an auto-associative feed-forward neural network (Scholz, 2005). We show the geophysical relevance of these techniques by application of each to a synthetic data set. Results are compared by inverting principal axes to determine deformation source parameters. Temporal variability in source parameters, estimated by each method, are also compared.

Problematic mobile phone use in adolescents: derivation of a short scale MPPUS-10.

PubMed

Foerster, Milena; Roser, Katharina; Schoeni, Anna; Röösli, Martin

2015-02-01

Our aim was to derive a short version of the Mobile Phone Problem Use Scale (MPPUS) using data from 412 adolescents of the Swiss HERMES (Health Effects Related to Mobile phonE use in adolescentS) cohort. A German version of the original MPPUS consisting of 27 items was shortened by principal component analysis (PCA) using baseline data collected in 2012. For confirmation, the PCA was carried out again with follow-up data 1 year later. PCA revealed four factors related to symptoms of addiction (Loss of Control, Withdrawal, Negative Life Consequences and Craving) and a fifth factor reflecting the social component of mobile phone use (Peer Dependence). The shortened scale (MPPUS-10) highly reflects the original MPPUS (Kendalls' Tau: 0.80 with 90% concordant pairs). Internal consistency of MPPUS-10 was good with Cronbach's alpha: 0.85. The results were confirmed using the follow-up data. The MPPUS-10 is a suitable instrument for research in adolescents. It will help to further clarify the definition of problematic mobile phone use in adolescents and explore similarities and differences to other technological addictions.

Chemical information obtained from Auger depth profiles by means of advanced factor analysis (MLCFA)

NASA Astrophysics Data System (ADS)

De Volder, P.; Hoogewijs, R.; De Gryse, R.; Fiermans, L.; Vennik, J.

1993-01-01

The advanced multivariate statistical technique "maximum likelihood common factor analysis (MLCFA)" is shown to be superior to "principal component analysis (PCA)" for decomposing overlapping peaks into their individual component spectra of which neither the number of components nor the peak shape of the component spectra is known. An examination of the maximum resolving power of both techniques, MLCFA and PCA, by means of artificially created series of multicomponent spectra confirms this finding unambiguously. Substantial progress in the use of AES as a chemical-analysis technique is accomplished through the implementation of MLCFA. Chemical information from Auger depth profiles is extracted by investigating the variation of the line shape of the Auger signal as a function of the changing chemical state of the element. In particular, MLCFA combined with Auger depth profiling has been applied to problems related to steelcord-rubber tyre adhesion. MLCFA allows one to elucidate the precise nature of the interfacial layer of reaction products between natural rubber vulcanized on a thin brass layer. This study reveals many interesting chemical aspects of the oxi-sulfidation of brass undetectable with classical AES.

Does adding ketamine to morphine patient-controlled analgesia safely improve post-thoracotomy pain?

PubMed

Mathews, Timothy J; Churchhouse, Antonia M D; Housden, Tessa; Dunning, Joel

2012-02-01

A best evidence topic in thoracic surgery was written according to a structured protocol. The question addressed was 'is the addition of ketamine to morphine patient-controlled analgesia (PCA) following thoracic surgery superior to morphine alone'. Altogether 201 papers were found using the reported search, of which nine represented the best evidence to answer the clinical question. The authors, journal, date and country of publication, patient group studied, study type, relevant outcomes and results of these papers are tabulated. This consisted of one systematic review of PCA morphine with ketamine (PCA-MK) trials, one meta-analysis of PCA-MK trials, four randomized controlled trials of PCA-MK, one meta-analysis of trials using a variety of peri-operative ketamine regimes and two cohort studies of PCA-MK. Main outcomes measured included pain score rated on visual analogue scale, morphine consumption and incidence of psychotomimetic side effects/hallucination. Two papers reported the measurements of respiratory function. This evidence shows that adding ketamine to morphine PCA is safe, with a reported incidence of hallucination requiring intervention of 2.9%, and a meta-analysis finding an incidence of all central nervous system side effects of 18% compared with 15% with morphine alone, P = 0.31, RR 1.27 with 95% CI (0.8-2.01). All randomized controlled trials of its use following thoracic surgery found no hallucination or psychological side effect. All five studies in thoracic surgery (n = 243) found reduced morphine requirements with PCA-MK. Pain scores were significantly lower in PCA-MK patients in thoracic surgery papers, with one paper additionally reporting increased patient satisfaction. However, no significant improvement was found in a meta-analysis of five papers studying PCA-MK in a variety of surgical settings. Both papers reporting respiratory outcomes found improved oxygen saturations and PaCO(2) levels in PCA-MK patients following thoracic surgery. We conclude that adding low-dose ketamine to morphine PCA is safe and post-thoracotomy may provide better pain control than PCA with morphine alone (PCA-MO), with reduced morphine consumption and possible improvement in respiratory function. These studies thus support the routine use of PCA-MK instead of PCA-MO to improve post-thoracotomy pain control.

Soy Consumption and the Risk of Prostate Cancer: An Updated Systematic Review and Meta-Analysis

PubMed Central

Ranard, Katherine M.; Jeon, Sookyoung; Erdman, John W.

2018-01-01

Prostate cancer (PCa) is the second most commonly diagnosed cancer in men, accounting for 15% of all cancers in men worldwide. Asian populations consume soy foods as part of a regular diet, which may contribute to the lower PCa incidence observed in these countries. This meta-analysis provides a comprehensive updated analysis that builds on previously published meta-analyses, demonstrating that soy foods and their isoflavones (genistein and daidzein) are associated with a lower risk of prostate carcinogenesis. Thirty articles were included for analysis of the potential impacts of soy food intake, isoflavone intake, and circulating isoflavone levels, on both primary and advanced PCa. Total soy food (p < 0.001), genistein (p = 0.008), daidzein (p = 0.018), and unfermented soy food (p < 0.001) intakes were significantly associated with a reduced risk of PCa. Fermented soy food intake, total isoflavone intake, and circulating isoflavones were not associated with PCa risk. Neither soy food intake nor circulating isoflavones were associated with advanced PCa risk, although very few studies currently exist to examine potential associations. Combined, this evidence from observational studies shows a statistically significant association between soy consumption and decreased PCa risk. Further studies are required to support soy consumption as a prophylactic dietary approach to reduce PCa carcinogenesis. PMID:29300347

ARLTS1 and Prostate Cancer Risk - Analysis of Expression and Regulation

PubMed Central

Siltanen, Sanna; Fischer, Daniel; Rantapero, Tommi; Laitinen, Virpi; Mpindi, John Patrick; Kallioniemi, Olli; Wahlfors, Tiina; Schleutker, Johanna

2013-01-01

Prostate cancer (PCa) is a heterogeneous trait for which several susceptibility loci have been implicated by genome-wide linkage and association studies. The genomic region 13q14 is frequently deleted in tumour tissues of both sporadic and familial PCa patients and is consequently recognised as a possible locus of tumour suppressor gene(s). Deletions of this region have been found in many other cancers. Recently, we showed that homozygous carriers for the T442C variant of the ARLTS1 gene (ADP-ribosylation factor-like tumour suppressor protein 1 or ARL11, located at 13q14) are associated with an increased risk for both unselected and familial PCa. Furthermore, the variant T442C was observed in greater frequency among malignant tissue samples, PCa cell lines and xenografts, supporting its role in PCa tumourigenesis. In this study, 84 PCa cases and 15 controls were analysed for ARLTS1 expression status in blood-derived RNA. A statistically significant (p = 0.0037) decrease of ARLTS1 expression in PCa cases was detected. Regulation of ARLTS1 expression was analysed with eQTL (expression quantitative trait loci) methods. Altogether fourteen significant cis-eQTLs affecting the ARLTS1 expression level were found. In addition, epistatic interactions of ARLTS1 genomic variants with genes involved in immune system processes were predicted with the MDR program. In conclusion, this study further supports the role of ARLTS1 as a tumour suppressor gene and reveals that the expression is regulated through variants localised in regulatory regions. PMID:23940804

Prostate health index (phi) and prostate cancer antigen 3 (PCA3) significantly improve diagnostic accuracy in patients undergoing prostate biopsy.

PubMed

Perdonà, Sisto; Bruzzese, Dario; Ferro, Matteo; Autorino, Riccardo; Marino, Ada; Mazzarella, Claudia; Perruolo, Giuseppe; Longo, Michele; Spinelli, Rosa; Di Lorenzo, Giuseppe; Oliva, Andrea; De Sio, Marco; Damiano, Rocco; Altieri, Vincenzo; Terracciano, Daniela

2013-02-15

Prostate health index (phi) and prostate cancer antigen 3 (PCA3) have been recently proposed as novel biomarkers for prostate cancer (PCa). We assessed the diagnostic performance of these biomarkers, alone or in combination, in men undergoing first prostate biopsy for suspicion of PCa. One hundred sixty male subjects were enrolled in this prospective observational study. PSA molecular forms, phi index (Beckman coulter immunoassay), PCA3 score (Progensa PCA3 assay), and other established biomarkers (tPSA, fPSA, and %fPSA) were assessed before patients underwent a 18-core first prostate biopsy. The discriminating ability between PCa-negative and PCa-positive biopsies of Beckman coulter phi and PCA3 score and other used biomarkers were determined. One hundred sixty patients met inclusion criteria. %p2PSA (p2PSA/fPSA × 100), phi and PCA3 were significantly higher in patients with PCa compared to PCa-negative group (median values: 1.92 vs. 1.55, 49.97 vs. 36.84, and 50 vs. 32, respectively, P ≤ 0.001). ROC curve analysis showed that %p2PSA, phi, and PCA3 are good indicator of malignancy (AUCs = 0.68, 0.71, and 0.66, respectively). A multivariable logistic regression model consisting of both the phi index and PCA3 score allowed to reach an overall diagnostic accuracy of 0.77. Decision curve analysis revealed that this "combined" marker achieved the highest net benefit over the examined range of the threshold probability. phi and PCA3 showed no significant difference in the ability to predict PCa diagnosis in men undergoing first prostate biopsy. However, diagnostic performance is significantly improved by combining phi and PCA3. Copyright © 2012 Wiley Periodicals, Inc.

Study of recognizing multiple persons' complicated hand gestures from the video sequence acquired by a moving camera

NASA Astrophysics Data System (ADS)

Dan, Luo; Ohya, Jun

2010-02-01

Recognizing hand gestures from the video sequence acquired by a dynamic camera could be a useful interface between humans and mobile robots. We develop a state based approach to extract and recognize hand gestures from moving camera images. We improved Human-Following Local Coordinate (HFLC) System, a very simple and stable method for extracting hand motion trajectories, which is obtained from the located human face, body part and hand blob changing factor. Condensation algorithm and PCA-based algorithm was performed to recognize extracted hand trajectories. In last research, this Condensation Algorithm based method only applied for one person's hand gestures. In this paper, we propose a principal component analysis (PCA) based approach to improve the recognition accuracy. For further improvement, temporal changes in the observed hand area changing factor are utilized as new image features to be stored in the database after being analyzed by PCA. Every hand gesture trajectory in the database is classified into either one hand gesture categories, two hand gesture categories, or temporal changes in hand blob changes. We demonstrate the effectiveness of the proposed method by conducting experiments on 45 kinds of sign language based Japanese and American Sign Language gestures obtained from 5 people. Our experimental recognition results show better performance is obtained by PCA based approach than the Condensation algorithm based method.

Age-related differences in early novelty processing: Using PCA to parse the overlapping anterior P2 and N2 components

PubMed Central

Daffner, Kirk R.; Alperin, Brittany R.; Mott, Katherine K.; Tusch, Erich; Holcomb, Phillip J.

2015-01-01

Previous work demonstrated age-associated increases in the anterior P2 and age-related decreases in the anterior N2 in response to novel stimuli. Principal component analysis (PCA) was used to determine if the inverse relationship between these components was due to their temporal and spatial overlap. PCA revealed an early anterior P2, sensitive to task relevance, and a late anterior P2, responsive to novelty, both exhibiting age-related amplitude increases. A PCA factor representing the anterior N2, sensitive to novelty, exhibited age-related amplitude decreases. The late P2 and N2 to novels inversely correlated. Larger late P2 amplitude to novels was associated with better behavioral performance. Age-related differences in the anterior P2 and N2 to novel stimuli likely represent age-associated changes in independent cognitive operations. Enhanced anterior P2 activity (indexing augmentation in motivational salience) may be a compensatory mechanism for diminished anterior N2 activity (indexing reduced ability of older adults to process ambiguous representations). PMID:25596483

Role of Genetic Testing for Inherited Prostate Cancer Risk: Philadelphia Prostate Cancer Consensus Conference 2017.

PubMed

Giri, Veda N; Knudsen, Karen E; Kelly, William K; Abida, Wassim; Andriole, Gerald L; Bangma, Chris H; Bekelman, Justin E; Benson, Mitchell C; Blanco, Amie; Burnett, Arthur; Catalona, William J; Cooney, Kathleen A; Cooperberg, Matthew; Crawford, David E; Den, Robert B; Dicker, Adam P; Eggener, Scott; Fleshner, Neil; Freedman, Matthew L; Hamdy, Freddie C; Hoffman-Censits, Jean; Hurwitz, Mark D; Hyatt, Colette; Isaacs, William B; Kane, Christopher J; Kantoff, Philip; Karnes, R Jeffrey; Karsh, Lawrence I; Klein, Eric A; Lin, Daniel W; Loughlin, Kevin R; Lu-Yao, Grace; Malkowicz, S Bruce; Mann, Mark J; Mark, James R; McCue, Peter A; Miner, Martin M; Morgan, Todd; Moul, Judd W; Myers, Ronald E; Nielsen, Sarah M; Obeid, Elias; Pavlovich, Christian P; Peiper, Stephen C; Penson, David F; Petrylak, Daniel; Pettaway, Curtis A; Pilarski, Robert; Pinto, Peter A; Poage, Wendy; Raj, Ganesh V; Rebbeck, Timothy R; Robson, Mark E; Rosenberg, Matt T; Sandler, Howard; Sartor, Oliver; Schaeffer, Edward; Schwartz, Gordon F; Shahin, Mark S; Shore, Neal D; Shuch, Brian; Soule, Howard R; Tomlins, Scott A; Trabulsi, Edouard J; Uzzo, Robert; Vander Griend, Donald J; Walsh, Patrick C; Weil, Carol J; Wender, Richard; Gomella, Leonard G

2018-02-01

Purpose Guidelines are limited for genetic testing for prostate cancer (PCA). The goal of this conference was to develop an expert consensus-driven working framework for comprehensive genetic evaluation of inherited PCA in the multigene testing era addressing genetic counseling, testing, and genetically informed management. Methods An expert consensus conference was convened including key stakeholders to address genetic counseling and testing, PCA screening, and management informed by evidence review. Results Consensus was strong that patients should engage in shared decision making for genetic testing. There was strong consensus to test HOXB13 for suspected hereditary PCA, BRCA1/2 for suspected hereditary breast and ovarian cancer, and DNA mismatch repair genes for suspected Lynch syndrome. There was strong consensus to factor BRCA2 mutations into PCA screening discussions. BRCA2 achieved moderate consensus for factoring into early-stage management discussion, with stronger consensus in high-risk/advanced and metastatic setting. Agreement was moderate to test all men with metastatic castration-resistant PCA, regardless of family history, with stronger agreement to test BRCA1/2 and moderate agreement to test ATM to inform prognosis and targeted therapy. Conclusion To our knowledge, this is the first comprehensive, multidisciplinary consensus statement to address a genetic evaluation framework for inherited PCA in the multigene testing era. Future research should focus on developing a working definition of familial PCA for clinical genetic testing, expanding understanding of genetic contribution to aggressive PCA, exploring clinical use of genetic testing for PCA management, genetic testing of African American males, and addressing the value framework of genetic evaluation and testing men at risk for PCA-a clinically heterogeneous disease.

Characterization of dissolved organic matter in Dongjianghu Lake by UV-visible absorption spectroscopy with multivariate analysis.

PubMed

Zhu, Yanzhong; Song, Yonghui; Yu, Huibin; Liu, Ruixia; Liu, Lusan; Lv, Chunjian

2017-08-08

UV-visible absorption spectroscopy coupled with principal component analysis (PCA) and hierarchical cluster analysis (HCA) was applied to characterize spectroscopic components, detect latent factors, and investigate spatial variations of dissolved organic matter (DOM) in a large-scale lake. Twelve surface water samples were collected from Dongjianghu Lake in China. DOM contained lignin and quinine moieties, carboxylic acid, microbial products, and aromatic and alkyl groups, which in the northern part of the lake was largely different from the southern part. Fifteen spectroscopic indices were deduced from the absorption spectra to indicate molecular weight or humification degree of DOM. The northern part of the lake presented the smaller molecular weight or the lower humification degree of DOM than the southern part. E 2/4 , E 3/4 , E 2/3 , and S 2 were latent factors of characterizing the molecular weight of DOM, while E 2/5 , E 3/5 , E 2/6 , E 4/5 , E 3/6 , and A 2/1 were latent factors of evaluating the humification degree of DOM. The UV-visible absorption spectroscopy combined with PCA and HCA may not only characterize DOM fractions of lakes, but may be transferred to other types of waterscape.

An experimental evaluation of the incidence of fitness-function/search-algorithm combinations on the classification performance of myoelectric control systems with iPCA tuning

PubMed Central

2013-01-01

Background The information of electromyographic signals can be used by Myoelectric Control Systems (MCSs) to actuate prostheses. These devices allow the performing of movements that cannot be carried out by persons with amputated limbs. The state of the art in the development of MCSs is based on the use of individual principal component analysis (iPCA) as a stage of pre-processing of the classifiers. The iPCA pre-processing implies an optimization stage which has not yet been deeply explored. Methods The present study considers two factors in the iPCA stage: namely A (the fitness function), and B (the search algorithm). The A factor comprises two levels, namely A1 (the classification error) and A2 (the correlation factor). Otherwise, the B factor has four levels, specifically B1 (the Sequential Forward Selection, SFS), B2 (the Sequential Floating Forward Selection, SFFS), B3 (Artificial Bee Colony, ABC), and B4 (Particle Swarm Optimization, PSO). This work evaluates the incidence of each one of the eight possible combinations between A and B factors over the classification error of the MCS. Results A two factor ANOVA was performed on the computed classification errors and determined that: (1) the interactive effects over the classification error are not significative (F0.01,3,72 = 4.0659 > f AB  = 0.09), (2) the levels of factor A have significative effects on the classification error (F0.02,1,72 = 5.0162 < f A  = 6.56), and (3) the levels of factor B over the classification error are not significative (F0.01,3,72 = 4.0659 > f B  = 0.08). Conclusions Considering the classification performance we found a superiority of using the factor A2 in combination with any of the levels of factor B. With respect to the time performance the analysis suggests that the PSO algorithm is at least 14 percent better than its best competitor. The latter behavior has been observed for a particular configuration set of parameters in the search algorithms. Future works will investigate the effect of these parameters in the classification performance, such as length of the reduced size vector, number of particles and bees used during optimal search, the cognitive parameters in the PSO algorithm as well as the limit of cycles to improve a solution in the ABC algorithm. PMID:24369728

The Effect of Phenazine-1-Carboxylic Acid on Mycelial Growth of Botrytis cinerea Produced by Pseudomonas aeruginosa LV Strain.

PubMed

Simionato, Ane S; Navarro, Miguel O P; de Jesus, Maria L A; Barazetti, André R; da Silva, Caroline S; Simões, Glenda C; Balbi-Peña, Maria I; de Mello, João C P; Panagio, Luciano A; de Almeida, Ricardo S C; Andrade, Galdino; de Oliveira, Admilton G

2017-01-01

One of the most important postharvest plant pathogens that affect strawberries, grapes and tomatoes is Botrytis cinerea , known as gray mold. The fungus remains in latent form until spore germination conditions are good, making infection control difficult, causing great losses in the whole production chain. This study aimed to purify and identify phenazine-1-carboxylic acid (PCA) produced by the Pseudomonas aeruginosa LV strain and to determine its antifungal activity against B. cinerea . The compounds produced were extracted with dichloromethane and passed through a chromatographic process. The purity level of PCA was determined by reversed-phase high-performance liquid chromatography semi-preparative. The structure of PCA was confirmed by nuclear magnetic resonance and electrospray ionization mass spectrometry. Antifungal activity was determined by the dry paper disk and minimum inhibitory concentration (MIC) methods and identified by scanning electron microscopy and confocal microscopy. The results showed that PCA inhibited mycelial growth, where MIC was 25 μg mL -1 . Microscopic analysis revealed a reduction in exopolysaccharide (EPS) formation, showing distorted and damaged hyphae of B. cinerea . The results suggested that PCA has a high potential in the control of B. cinerea and inhibition of EPS (important virulence factor). This natural compound is a potential alternative to postharvest control of gray mold disease.

Bayesian inference of the number of factors in gene-expression analysis: application to human virus challenge studies.

PubMed

Chen, Bo; Chen, Minhua; Paisley, John; Zaas, Aimee; Woods, Christopher; Ginsburg, Geoffrey S; Hero, Alfred; Lucas, Joseph; Dunson, David; Carin, Lawrence

2010-11-09

Nonparametric Bayesian techniques have been developed recently to extend the sophistication of factor models, allowing one to infer the number of appropriate factors from the observed data. We consider such techniques for sparse factor analysis, with application to gene-expression data from three virus challenge studies. Particular attention is placed on employing the Beta Process (BP), the Indian Buffet Process (IBP), and related sparseness-promoting techniques to infer a proper number of factors. The posterior density function on the model parameters is computed using Gibbs sampling and variational Bayesian (VB) analysis. Time-evolving gene-expression data are considered for respiratory syncytial virus (RSV), Rhino virus, and influenza, using blood samples from healthy human subjects. These data were acquired in three challenge studies, each executed after receiving institutional review board (IRB) approval from Duke University. Comparisons are made between several alternative means of per-forming nonparametric factor analysis on these data, with comparisons as well to sparse-PCA and Penalized Matrix Decomposition (PMD), closely related non-Bayesian approaches. Applying the Beta Process to the factor scores, or to the singular values of a pseudo-SVD construction, the proposed algorithms infer the number of factors in gene-expression data. For real data the "true" number of factors is unknown; in our simulations we consider a range of noise variances, and the proposed Bayesian models inferred the number of factors accurately relative to other methods in the literature, such as sparse-PCA and PMD. We have also identified a "pan-viral" factor of importance for each of the three viruses considered in this study. We have identified a set of genes associated with this pan-viral factor, of interest for early detection of such viruses based upon the host response, as quantified via gene-expression data.

Multilevel principal component analysis (mPCA) in shape analysis: A feasibility study in medical and dental imaging.

PubMed

Farnell, D J J; Popat, H; Richmond, S

2016-06-01

Methods used in image processing should reflect any multilevel structures inherent in the image dataset or they run the risk of functioning inadequately. We wish to test the feasibility of multilevel principal components analysis (PCA) to build active shape models (ASMs) for cases relevant to medical and dental imaging. Multilevel PCA was used to carry out model fitting to sets of landmark points and it was compared to the results of "standard" (single-level) PCA. Proof of principle was tested by applying mPCA to model basic peri-oral expressions (happy, neutral, sad) approximated to the junction between the mouth/lips. Monte Carlo simulations were used to create this data which allowed exploration of practical implementation issues such as the number of landmark points, number of images, and number of groups (i.e., "expressions" for this example). To further test the robustness of the method, mPCA was subsequently applied to a dental imaging dataset utilising landmark points (placed by different clinicians) along the boundary of mandibular cortical bone in panoramic radiographs of the face. Changes of expression that varied between groups were modelled correctly at one level of the model and changes in lip width that varied within groups at another for the Monte Carlo dataset. Extreme cases in the test dataset were modelled adequately by mPCA but not by standard PCA. Similarly, variations in the shape of the cortical bone were modelled by one level of mPCA and variations between the experts at another for the panoramic radiographs dataset. Results for mPCA were found to be comparable to those of standard PCA for point-to-point errors via miss-one-out testing for this dataset. These errors reduce with increasing number of eigenvectors/values retained, as expected. We have shown that mPCA can be used in shape models for dental and medical image processing. mPCA was found to provide more control and flexibility when compared to standard "single-level" PCA. Specifically, mPCA is preferable to "standard" PCA when multiple levels occur naturally in the dataset. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Regulation of tissue factor in NT2 germ cell tumor cells by cisplatin chemotherapy.

PubMed

Jacobsen, Christine; Oechsle, Karin; Hauschild, Jessica; Steinemann, Gustav; Spath, Brigitte; Bokemeyer, Carsten; Ruf, Wolfram; Honecker, Friedemann; Langer, Florian

2015-09-01

Patients with germ cell tumors (GCTs) receiving cisplatin-based chemotherapy are at increased risk of thrombosis, but the underlying cellular and molecular mechanisms remain obscure. To study baseline tissue factor (TF) expression by GCT cell lines and its modulation by cisplatin treatment. TF expression was assessed by single-stage clotting and thrombin generation assay, flow cytometry, ELISA, and Western blot analysis. Cell cycle analysis and detection of phosphatidylserine (PS) membrane exposure were carried out by flow cytometry. TF mRNA was analyzed by quantitative RT-PCR. Significant expression of TF-specific procoagulant activity (PCA) was detected on three non-seminoma (NT2, 2102Ep, NCCIT) and one seminoma cell line (TCam-2). Treatment with 0.4μM cisplatin (corresponding to the IC50) for 48hrs increased TF PCA on NT2 cells 3-fold, an effect that was largely independent of PS exposure and that could not be explained by translocation of active TF from intracellular storage pools. Cisplatin-induced TF PCA expression in NT2 cells did not occur before 12hrs, but was steady thereafter and accompanied by a 2-fold increase in total and surface-located TF antigen. Importantly, increased TF gene transcription or production and release of an intermediate factor were not involved in this process. Cell cycle analysis suggested that cisplatin-induced G2/M arrest resulted in an accumulation of procoagulant TF on the membrane surface of NT2 cells. In addition to induction of apoptosis/necrosis with PS-mediated activation of preformed TF, cisplatin may alter the procoagulant phenotype of GCT cells through an increase in total cellular TF antigen. Copyright © 2015 Elsevier Ltd. All rights reserved.

Promoter methylation of the immune checkpoint receptor PD-1 (PDCD1) is an independent prognostic biomarker for biochemical recurrence-free survival in prostate cancer patients following radical prostatectomy.

PubMed

Goltz, Diane; Gevensleben, Heidrun; Dietrich, Jörn; Ellinger, Jörg; Landsberg, Jennifer; Kristiansen, Glen; Dietrich, Dimo

2016-01-01

Biomarkers that facilitate the prediction of disease recurrence in prostate cancer (PCa) may enable physicians to personalize treatment for individual patients. In the current study, PD-1 ( PDCD1 ) promoter methylation was assessed in a cohort of 498 PCa patients included in The Cancer Genome Atlas (TCGA) and a second cohort of 300 PCa cases treated at the University Hospital of Bonn. In the TCGA cohort, the PD-1 promoter was significantly hypermethylated in carcinomas versus normal prostatic epithelium (55.5% vs. 38.2%, p < 0.001) and PD-1 methylation ( mPD-1 ) inversely correlated with PD-1 mRNA expression in PCa (Spearman's ρ = -0.415, p < 0.001). In both cohorts, mPD-1 significantly correlated with preoperative prostate specific antigen (PSA). In univariate Cox Proportional Hazard analysis, mPD-1 served as a significant prognostic factor for biochemical recurrence (BCR)-free survival (Hazard ratio: HR = 2.35 [1.35-4.10], p = 0.003, n = 410) in the TCGA cohort. In multivariate analysis, mPD-1 was shown to add significant independent prognostic information adjunct to pathologic tumor category (pT) and Gleason grading group (HR = 2.08 [1.16-3.74], p = 0.014, n = 350). PD-1 promoter methylation analyses could thus potentially aid the identification of patients which might benefit from adjuvant treatment after radical prostatectomy. Moreover, our data suggest an intrinsic role of PD-1 in PCa carcinogenesis and disease progression, which needs to be addressed in future studies.

Isolation–By–Distance–and–Time in a stepping–stone model

PubMed Central

Duforet-Frebourg, Nicolas; Slatkin, Montgomery

2015-01-01

With the great advances in ancient DNA extraction, genetic data are now obtained from geographically separated individuals from both present and past. However, population genetics theory about the joint effect of space and time has not been thoroughly studied. Based on the classical stepping–stone model, we develop the theory of Isolation by Distance and Time. We derive the correlation of allele frequencies between demes in the case where ancient samples are present, and investigate the impact of edge effects with forward–in–time simulations. We also derive results about coalescent times in circular and toroidal models. As one of the most common ways to investigate population structure is principal components analysis (PCA), we evaluate the impact of our theory on PCA plots. Our results demonstrate that time between samples is an important factor. Ancient samples tend to be drawn to the center of a PCA plot. PMID:26592162

No Association Between Variant N-acetyltransferase Genes, Cigarette Smoking and Prostate Cancer Susceptibility Among Men of African Descent

PubMed Central

Kidd, La Creis Renee; VanCleave, Tiva T.; Doll, Mark A.; Srivastava, Daya S.; Thacker, Brandon; Komolafe, Oyeyemi; Pihur, Vasyl; Brock, Guy N.; Hein, David W.

2011-01-01

Objective We evaluated the individual and combination effects of NAT1, NAT2 and tobacco smoking in a case-control study of 219 incident prostate cancer (PCa) cases and 555 disease-free men. Methods Allelic discriminations for 15 NAT1 and NAT2 loci were detected in germ-line DNA samples using Taqman polymerase chain reaction (PCR) assays. Single gene, gene-gene and gene-smoking interactions were analyzed using logistic regression models and multi-factor dimensionality reduction (MDR) adjusted for age and subpopulation stratification. MDR involves a rigorous algorithm that has ample statistical power to assess and visualize gene-gene and gene-environment interactions using relatively small samples sizes (i.e., 200 cases and 200 controls). Results Despite the relatively high prevalence of NAT1*10/*10 (40.1%), NAT2 slow (30.6%), and NAT2 very slow acetylator genotypes (10.1%) among our study participants, these putative risk factors did not individually or jointly increase PCa risk among all subjects or a subset analysis restricted to tobacco smokers. Conclusion Our data do not support the use of N-acetyltransferase genetic susceptibilities as PCa risk factors among men of African descent; however, subsequent studies in larger sample populations are needed to confirm this finding. PMID:21709725

Nonlinear Principal Components Analysis: Introduction and Application

ERIC Educational Resources Information Center

Linting, Marielle; Meulman, Jacqueline J.; Groenen, Patrick J. F.; van der Koojj, Anita J.

2007-01-01

The authors provide a didactic treatment of nonlinear (categorical) principal components analysis (PCA). This method is the nonlinear equivalent of standard PCA and reduces the observed variables to a number of uncorrelated principal components. The most important advantages of nonlinear over linear PCA are that it incorporates nominal and ordinal…

The fractal characteristic of facial anthropometric data for developing PCA fit test panels for youth born in central China.

PubMed

Yang, Lei; Wei, Ran; Shen, Henggen

2017-01-01

New principal component analysis (PCA) respirator fit test panels had been developed for current American and Chinese civilian workers based on anthropometric surveys. The PCA panels used the first two principal components (PCs) obtained from a set of 10 facial dimensions. Although the PCA panels for American and Chinese subjects adopted the bivairate framework with two PCs, the number of the PCs retained in the PCA analysis was different between Chinese subjects and Americans. For the Chinese youth group, the third PC should be retained in the PCA analysis for developing new fit test panels. In this article, an additional number label (ANL) is used to explain the third PC in PCA analysis when the first two PCs are used to construct the PCA half-facepiece respirator fit test panel for Chinese group. The three-dimensional box-counting method is proposed to estimate the ANLs by calculating fractal dimensions of the facial anthropometric data of the Chinese youth. The linear regression coefficients of scale-free range R 2 are all over 0.960, which demonstrates that the facial anthropometric data of the Chinese youth has fractal characteristic. The youth subjects born in Henan province has an ANL of 2.002, which is lower than the composite facial anthropometric data of Chinese subjects born in many provinces. Hence, Henan youth subjects have the self-similar facial anthropometric characteristic and should use the particular ANL (2.002) as the important tool along with using the PCA panel. The ANL method proposed in this article not only provides a new methodology in quantifying the characteristics of facial anthropometric dimensions for any ethnic/racial group, but also extends the scope of PCA panel studies to higher dimensions.

miR-188-5p inhibits tumour growth and metastasis in prostate cancer by repressing LAPTM4B expression.

PubMed

Zhang, Hongtuan; Qi, Shiyong; Zhang, Tao; Wang, Andi; Liu, Ranlu; Guo, Jia; Wang, Yuzhuo; Xu, Yong

2015-03-20

Elucidation of the molecular targets and pathways regulated by the tumour-suppressive miRNAs can shed light on the oncogenic and metastatic processes in prostate cancer (PCa). Using miRNA profiling analysis, we find that miR-188-5p was significantly down-regulated in metastatic PCa. Down-regulation of miR-188-5p is an independent prognostic factor for poor overall and biochemical recurrence-free survival. Restoration of miR-188-5p in PCa cells (PC-3 and LNCaP) significantly suppresses proliferation, migration and invasion in vitro and inhibits tumour growth and metastasis in vivo. We also find overexpression of miR-188-5p in PC-3 cells can significantly enhance the cells' chemosensitivity to adriamycin. LAPTM4B is subsequently identified as a direct target of miR-188-5p in PCa, and is found to be significantly over-expressed in PCa. Knockdown of LAPTM4B phenotypically copies miR-188-5p-induced phenotypes, whereas ectopic expression of LAPTM4B reverses the effects of miR-188-5p. We also find that restoration of miR-188-5p can inhibit the PI3K/AKT signaling pathway via the suppression of LAPTM4B. Taken together, this is the first report unveils that miR-188-5p acts as a tumour suppressor in PCa and may therefore serve as a useful therapeutic target for the development of new anticancer therapy.

From palmistry to anthropometry: can 2nd to 4th digit length (2D:4D) predict the risk of prostate cancer?

PubMed

Salomão, Layla; Figueiredo, Rui Teófilo; Oliveira Santos, Rafael; Damião, Ronaldo; da Silva, Eloisio Alexsandro

2014-01-01

The 2nd to 4th digit length (2D:4D) is inversely related to androgen exposure during the fetal period, which may represent a risk factor for several steroid-related diseases. We aimed to evaluate the relationship between 2D:4D ratio and the risk of developing prostate cancer (PCa). We assessed the 2D:4D ratio of 474 men >40 years old, stratified into three groups: group 1 (n = 222) patients with PCa, group 2 (n = 82) subjects with high risk of PCa, and group 3 (n = 170) men with low risk of PCa. Subjects were submitted to a digital picture of the ventral surface of the right hand and 2nd and 4th fingers measurements were determined by the distance from the proximal crease to the tip using computer-assisted analysis. The mean serum prostate-specific antigen level was 7.5 ng/ml in the high-risk group and 0.92 ng/ml in the low-risk group (p < 0.05). The mean 2D:4D ratios were 0.96 ± 0.04, 0.97 ± 0.04 and 0.96 ± 0.04 for the PCa, high-risk and low-risk groups, respectively, and no difference was found among the three groups (p = 0.12). Anthropometry of the hand using the 2D:4D ratio is not a predictor of PCa. 2013 S. Karger AG, Basel.

Patterns in longitudinal growth of refraction in Southern Chinese children: cluster and principal component analysis.

PubMed

Chen, Yanxian; Chang, Billy Heung Wing; Ding, Xiaohu; He, Mingguang

2016-11-22

In the present study we attempt to use hypothesis-independent analysis in investigating the patterns in refraction growth in Chinese children, and to explore the possible risk factors affecting the different components of progression, as defined by Principal Component Analysis (PCA). A total of 637 first-born twins in Guangzhou Twin Eye Study with 6-year annual visits (baseline age 7-15 years) were available in the analysis. Cluster 1 to 3 were classified after a partitioning clustering, representing stable, slow and fast progressing groups of refraction respectively. Baseline age and refraction, paternal refraction, maternal refraction and proportion of two myopic parents showed significant differences across the three groups. Three major components of progression were extracted using PCA: "Average refraction", "Acceleration" and the combination of "Myopia stabilization" and "Late onset of refraction progress". In regression models, younger children with more severe myopia were associated with larger "Acceleration". The risk factors of "Acceleration" included change of height and weight, near work, and parental myopia, while female gender, change of height and weight were associated with "Stabilization", and increased outdoor time was related to "Late onset of refraction progress". We therefore concluded that genetic and environmental risk factors have different impacts on patterns of refraction progression.

Patterns in longitudinal growth of refraction in Southern Chinese children: cluster and principal component analysis

PubMed Central

Chen, Yanxian; Chang, Billy Heung Wing; Ding, Xiaohu; He, Mingguang

2016-01-01

In the present study we attempt to use hypothesis-independent analysis in investigating the patterns in refraction growth in Chinese children, and to explore the possible risk factors affecting the different components of progression, as defined by Principal Component Analysis (PCA). A total of 637 first-born twins in Guangzhou Twin Eye Study with 6-year annual visits (baseline age 7–15 years) were available in the analysis. Cluster 1 to 3 were classified after a partitioning clustering, representing stable, slow and fast progressing groups of refraction respectively. Baseline age and refraction, paternal refraction, maternal refraction and proportion of two myopic parents showed significant differences across the three groups. Three major components of progression were extracted using PCA: “Average refraction”, “Acceleration” and the combination of “Myopia stabilization” and “Late onset of refraction progress”. In regression models, younger children with more severe myopia were associated with larger “Acceleration”. The risk factors of “Acceleration” included change of height and weight, near work, and parental myopia, while female gender, change of height and weight were associated with “Stabilization”, and increased outdoor time was related to “Late onset of refraction progress”. We therefore concluded that genetic and environmental risk factors have different impacts on patterns of refraction progression. PMID:27874105

Variants of early-onset restrictive eating disturbances in middle childhood.

PubMed

Kurz, Susanne; van Dyck, Zoé; Dremmel, Daniela; Munsch, Simone; Hilbert, Anja

2016-01-01

This study sought to determine the factor structure of the newly developed self-report screening questionnaire Eating Disturbances in Youth-Questionnaire (EDY-Q) as well as to report the distribution of variants of early-onset restrictive eating disturbances characteristic of avoidant/restrictive food intake disorder (ARFID) in a middle childhood population sample. Using the EDY-Q, a total of 1,444 children aged 8-13 years were screened in elementary schools in Switzerland via self-report. The factor analysis of the 12 items covering ARFID related symptoms was performed using a principal component analysis (PCA). The PCA showed a four factor solution, with clear allocation to the scales covering three variants of early-onset restrictive eating disturbances and weight problems. Inadequate overall food intake was reported by 19.3% of the children, a limited accepted amount of food by 26.1%, and food avoidance based on a specific underlying fear by 5.0%. The postulated factor structure of the EDY-Q was confirmed, further supporting the existence of distinct variants of early-onset restrictive eating disturbances. Avoidant/restrictive eating behavior seems to be a common experience in middle childhood, but results have to be confirmed using validated interviews. © 2015 Wiley Periodicals, Inc.

Time-dependent analysis of dosage delivery information for patient-controlled analgesia services.

PubMed

Kuo, I-Ting; Chang, Kuang-Yi; Juan, De-Fong; Hsu, Steen J; Chan, Chia-Tai; Tsou, Mei-Yung

2018-01-01

Pain relief always plays the essential part of perioperative care and an important role of medical quality improvement. Patient-controlled analgesia (PCA) is a method that allows a patient to self-administer small boluses of analgesic to relieve the subjective pain. PCA logs from the infusion pump consisted of a lot of text messages which record all events during the therapies. The dosage information can be extracted from PCA logs to provide easily understanding features. The analysis of dosage information with time has great help to figure out the variance of a patient's pain relief condition. To explore the trend of pain relief requirement, we developed a PCA dosage information generator (PCA DIG) to extract meaningful messages from PCA logs during the first 48 hours of therapies. PCA dosage information including consumption, delivery, infusion rate, and the ratio between demand and delivery is presented with corresponding values in 4 successive time frames. Time-dependent statistical analysis demonstrated the trends of analgesia requirements decreased gradually along with time. These findings are compatible with clinical observations and further provide valuable information about the strategy to customize postoperative pain management.

The Patient-Reported Information Multidimensional Exploration (PRIME) Framework for Investigating Emotions and Other Factors of Prostate Cancer Patients with Low Intermediate Risk Based on Online Cancer Support Group Discussions.

PubMed

Bandaragoda, Tharindu; Ranasinghe, Weranja; Adikari, Achini; de Silva, Daswin; Lawrentschuk, Nathan; Alahakoon, Damminda; Persad, Raj; Bolton, Damien

2018-06-01

This study aimed to use the Patient Reported Information Multidimensional Exploration (PRIME) framework, a novel ensemble of machine-learning and deep-learning algorithms, to extract, analyze, and correlate self-reported information from Online Cancer Support Groups (OCSG) by patients (and partners of patients) with low intermediate-risk prostate cancer (PCa) undergoing radical prostatectomy (RP), external beam radiotherapy (EBRT), and active surveillance (AS), and to investigate its efficacy in quality-of-life (QoL) and emotion measures. From patient-reported information on 10 OCSG, the PRIME framework automatically filtered and extracted conversations on low intermediate-risk PCa with active user participation. Side effects as well as emotional and QoL outcomes for 6084 patients were analyzed. Side-effect profiles differed between the methods analyzed, with men after RP having more urinary and sexual side effects and men after EBRT having more bowel symptoms. Key findings from the analysis of emotional expressions showed that PCa patients younger than 40 years expressed significantly high positive and negative emotions compared with other age groups, that partners of patients expressed more negative emotions than the patients, and that selected cohorts (< 40 years, > 70 years, partners of patients) have frequently used the same terms to express their emotions, which is indicative of QoL issues specific to those cohorts. Despite recent advances in patient-centerd care, patient emotions are largely overlooked, especially in younger men with a diagnosis of PCa and their partners. The authors present a novel approach, the PRIME framework, to extract, analyze, and correlate key patient factors. This framework improves understanding of QoL and identifies low intermediate-risk PCa patients who require additional support.

Occupation, industry, and the risk of prostate cancer: a case-control study in Montréal, Canada.

PubMed

Sauvé, Jean-François; Lavoué, Jérôme; Parent, Marie-Élise

2016-10-21

Age, family history and ancestry are the only recognized risk factors for prostate cancer (PCa) but a role for environmental factors is suspected. Due to the lack of knowledge on the etiological factors for PCa, studies that are both hypothesis-generating and confirmatory are still needed. This study explores relationships between employment, by occupation and industry, and PCa risk. Cases were 1937 men aged ≤75 years with incident PCa diagnosed across Montreal French hospitals in 2005-2009. Controls were 1994 men recruited concurrently from electoral lists of French-speaking Montreal residents, frequency-matched to cases by age. In-person interviews elicited occupational histories. Unconditional logistic regression estimated odds ratios (OR) and 95 % confidence intervals (CI) for the association between employment across 696 occupations and 613 industries and PCa risk, adjusting for potential confounders. Multinomial logistic models assessed risks by PCa grade. Semi-Bayes (SB) adjustment accounted for the large number of associations evaluated. Consistently positive associations-and generally robust to SB adjustment-were found for occupations in forestry and logging (OR 1.9, 95 % CI: 1.2-3.0), social sciences (OR 1.6, 95 % CI: 1.1-2.2) and for police officers and detectives (OR: 1.8, 95 % CI 1.1-2.9). Occupations where elevated risk of high grade PCa was found included gasoline station attendants (OR 4.3, 95 % CI 1.8-10.4) and textile processing occupations (OR 1.8, 95 % CI 1.1-3.2). Aside from logging, industries with elevated PCa risk included provincial government and financial institutions. Occupations with reduced risk included farmers (OR 0.6, 95 % CI 0.4-1.0) and aircraft maintenance workers (OR 0.1, 95 % CI 0.0-0.7). Excess PCa risks were observed across several occupations, including predominantly white collar workers. Further analyses will focus on specific occupational exposures.

Immunoseroproteomic Profiling in African American Men with Prostate Cancer: Evidence for an Autoantibody Response to Glycolysis and Plasminogen-Associated Proteins*

PubMed Central

Sanchez, Tino W.; Zhang, Guangyu; Li, Jitian; Dai, Liping; Mirshahidi, Saied; Wall, Nathan R.; Yates, Clayton; Wilson, Colwick; Montgomery, Susanne; Zhang, Jian-Ying; Casiano, Carlos A.

2016-01-01

African American (AA) men suffer from a disproportionately high incidence and mortality of prostate cancer (PCa) compared with other racial/ethnic groups. Despite these disparities, African American men are underrepresented in clinical trials and in studies on PCa biology and biomarker discovery. We used immunoseroproteomics to profile antitumor autoantibody responses in AA and European American (EA) men with PCa, and explored differences in these responses. This minimally invasive approach detects autoantibodies to tumor-associated antigens that could serve as clinical biomarkers and immunotherapeutic agents. Sera from AA and EA men with PCa were probed by immunoblotting against PC3 cell proteins, with AA sera showing stronger immunoreactivity. Mass spectrometry analysis of immunoreactive protein spots revealed that several AA sera contained autoantibodies to a number of proteins associated with both the glycolysis and plasminogen pathways, particularly to alpha-enolase (ENO1). The proteomic data is deposited in ProteomeXchange with identifier PXD003968. Analysis of sera from 340 racially diverse men by enzyme-linked immunosorbent assays (ELISA) showed higher frequency of anti-ENO1 autoantibodies in PCa sera compared with control sera. We observed differences between AA-PCa and EA-PCa patients in their immunoreactivity against ENO1. Although EA-PCa sera reacted with higher frequency against purified ENO1 in ELISA and recognized by immunoblotting the endogenous cellular ENO1 across a panel of prostate cell lines, AA-PCa sera reacted weakly against this protein by ELISA but recognized it by immunoblotting preferentially in metastatic cell lines. These race-related differences in immunoreactivity to ENO1 could not be accounted by differential autoantibody recognition of phosphoepitopes within this antigen. Proteomic analysis revealed differences in the posttranslational modification profiles of ENO1 variants differentially recognized by AA-PCa and EA-PCa sera. These intriguing results suggest the possibility of race-related differences in the antitumor autoantibody response in PCa, and have implications for defining novel biological determinants of PCa health disparities. PMID:27742740

Applying parallel factor analysis and Tucker-3 methods on sensory and instrumental data to establish preference maps: case study on sweet corn varieties.

PubMed

Gere, Attila; Losó, Viktor; Györey, Annamária; Kovács, Sándor; Huzsvai, László; Nábrádi, András; Kókai, Zoltán; Sipos, László

2014-12-01

Traditional internal and external preference mapping methods are based on principal component analysis (PCA). However, parallel factor analysis (PARAFAC) and Tucker-3 methods could be a better choice. To evaluate the methods, preference maps of sweet corn varieties will be introduced. A preference map of eight sweet corn varieties was established using PARAFAC and Tucker-3 methods. Instrumental data were also integrated into the maps. The triplot created by the PARAFAC model explains better how odour is separated from texture or appearance, and how some varieties are separated from others. Internal and external preference maps were created using parallel factor analysis (PARAFAC) and Tucker-3 models employing both sensory (trained panel and consumers) and instrumental parameters simultaneously. Triplots of the applied three-way models have a competitive advantage compared to the traditional biplots of the PCA-based external preference maps. The solution of PARAFAC and Tucker-3 is very similar regarding the interpretation of the first and third factors. The main difference is due to the second factor as it differentiated the attributes better. Consumers who prefer 'super sweet' varieties (they place great emphasis especially on taste) are much younger and have significantly higher incomes, and buy sweet corn products rarely (once a month). Consumers who consume sweet corn products mainly because of their texture and appearance are significantly older and include a higher ratio of men. © 2014 Society of Chemical Industry.

Stability of Nonlinear Principal Components Analysis: An Empirical Study Using the Balanced Bootstrap

ERIC Educational Resources Information Center

Linting, Marielle; Meulman, Jacqueline J.; Groenen, Patrick J. F.; van der Kooij, Anita J.

2007-01-01

Principal components analysis (PCA) is used to explore the structure of data sets containing linearly related numeric variables. Alternatively, nonlinear PCA can handle possibly nonlinearly related numeric as well as nonnumeric variables. For linear PCA, the stability of its solution can be established under the assumption of multivariate…

Continuous Metabolic Syndrome Scores for Children Using Salivary Biomarkers.

PubMed

Shi, Ping; Goodson, J Max; Hartman, Mor-Li; Hasturk, Hatice; Yaskell, Tina; Vargas, Jorel; Cugini, Maryann; Barake, Roula; Alsmadi, Osama; Al-Mutawa, Sabiha; Ariga, Jitendra; Soparkar, Pramod; Behbehani, Jawad; Behbehani, Kazem; Welty, Francine

2015-01-01

Binary definitions of the metabolic syndrome based on the presence of a particular number of individual risk factors are limited, particularly in the pediatric population. To address this limitation, we aimed at constructing composite and continuous metabolic syndrome scores (cmetS) to represent an overall measure of metabolic syndrome (MetS) in a large cohort of metabolically at-risk children, focusing on the use of the usual clinical parameters (waist circumference (WC) and systolic blood pressure (SBP), supplemented with two salivary surrogate variables (glucose and high density lipoprotein cholesterol (HDLC). Two different approaches used to create the scores were evaluated in comparison. Data from 8,112 Kuwaiti children (10.00 ± 0.67 years) were used to construct two cmetS for each subject. The first cmetS (cmetS-Z) was created by summing standardized residuals of each variable regressed on age and gender; and the second cmetS (cmetS-PCA) was defined as the first principal component from gender-specific principal component analysis based on the four variables. There was a graded relationship between both scores and the number of adverse risk factors. The areas under the curve using cmetS-Z and cmetS-PCA as predictors for severe metabolic syndrome (defined as the presence of ≥3 metabolic risk factors) were 0.935 and 0.912, respectively. cmetS-Z was positively associated with WC, SBP, and glucose, but inversely associated with HDLC. Except for the lack of association with glucose, cmetS-PCA was similar to cmetS-Z in boys, but had minimum loading on HDLC in girls. Analysis using quantile regression showed an inverse association of fitness level with cmetS-PCA (p = 0.001 for boys; p = 0.002 for girls), and comparison of cmetS-Z and cmetS-PCA suggested that WC and SBP were main contributory components. Significant alterations in the relationship between cmetS and salivary adipocytokines were demonstrated in overweight and obese children as compared to underweight and normal-weight children. We have derived continuous summary scores for MetS from a large-scale pediatric study using two different approaches, incorporating salivary measures as surrogate for plasma measures. The derived scores were viable expressions of metabolic risk, and can be utilized to study the relationships of MetS with various aspects of the metabolic disease process.

Associations of Plasma Concentrations of Dichlorodiphenyldichloroethylene and Polychlorinated Biphenyls with Prostate Cancer: A Case–Control Study in Guadeloupe (French West Indies)

PubMed Central

Emeville, Elise; Giusti, Arnaud; Coumoul, Xavier; Thomé, Jean-Pierre; Blanchet, Pascal

2014-01-01

Background: Long-term exposure to persistent pollutants with hormonal properties (endocrine-disrupting chemicals; EDCs) may contribute to the risk of prostate cancer (PCa). However, epidemiological evidence remains limited. Objectives: We investigated the relationship between PCa and plasma concentrations of universally widespread pollutants, in particular p,p´-dichlorodiphenyl dichloroethene (DDE) and the non-dioxin-like polychlorinated biphenyl congener 153 (PCB-153). Methods: We evaluated 576 men with newly diagnosed PCa (before treatment) and 655 controls in Guadeloupe (French West Indies). Exposure was analyzed according to case–control status. Associations were assessed by unconditional logistic regression analysis, controlling for confounding factors. Missing data were handled by multiple imputation. Results: We estimated a significant positive association between DDE and PCa [adjusted odds ratio (OR) = 1.53; 95% CI: 1.02, 2.30 for the highest vs. lowest quintile of exposure; ptrend = 0.01]. PCB-153 was inversely associated with PCa (OR = 0.30; 95% CI: 0.19, 0.47 for the highest vs. lowest quintile of exposure values; ptrend < 0.001). Also, PCB-153 was more strongly associated with low-grade than with high-grade PCa. Conclusions: Associations of PCa with DDE and PCB-153 were in opposite directions. This may reflect differences in the mechanisms of action of these EDCs; and although our findings need to be replicated in other populations, they are consistent with complex effects of EDCs on human health. Citation: Emeville E, Giusti A, Coumoul X, Thomé JP, Blanchet P, Multigner L. 2015. Associations of plasma concentrations of dichlorodiphenyldichloroethylene and polychlorinated biphenyls with prostate cancer: a case–control study in Guadeloupe (French West Indies). Environ Health Perspect 123:317–323; http://dx.doi.org/10.1289/ehp.1408407 PMID:25493337

Targeting IκB kinase β/NF-κB signaling in human prostate cancer by a novel IκB kinase β inhibitor CmpdA

PubMed Central

Zhang, Yanting; Lapidus, Rena G.; Liu, Peiyan; Choi, Eun Yong; Adediran, Samusi; Hussain, Arif; Wang, Xinghuan; Liu, Xuefeng; Dan, Han C.

2016-01-01

NF-κB plays an important role in many types of cancer, including prostate cancer (PCa), but the role of the upstream kinase of NF-κB, IKKβ, in PCa has not been fully documented, nor are there any effective IKKβ inhibitors used in clinical settings. Here, we have shown that IKKβ activity is mediated by multiple kinases including IKKα in human PCa cell lines that express activated IKKβ. Immunohistochemical analysis (IHC) of human PCa tissue microarrays (TMA) demonstrates that phosphorylation of IKKα/β within its activation loop gradually increases in low to higher stage tumors as compared to normal tissue. The expression of cell proliferation and survival markers (Ki67, Survivin), epithelial-to-mesenchymal transition (EMT) markers (Slug, Snail), as well as cancer stem cell (CSC) related transcription factors (Nanog, Sox2, Oct-4), also increase in parallel among the respective TMA samples analyzed. IKKβ, but not NF-κB, is found to regulate Nanog, which, in turn, modulates the levels of Oct4, Sox2, Snail and Slug, indicating an essential role of IKKβ in regulating cancer stem cells and EMT. The novel IKKβ inhibitor CmpdA inhibits constitutively activated IKKβ/NF-κB signaling, leading to induction of apoptosis and inhibition of proliferation, migration and stemness in these cells. CmpdA also significantly inhibits tumor growth in xenografts without causing apparent in vivo toxicity. Furthermore, CmpdA and docetaxel act synergistically to inhibit proliferation of PCa cells. These results indicate that IKKβ plays a pivotal role in PCa, and targeting IKKβ, including in combination with docetaxel, may be a potentially useful strategy for treating advanced PCa. PMID:27196761

DWI-associated entire-tumor histogram analysis for the differentiation of low-grade prostate cancer from intermediate-high-grade prostate cancer.

PubMed

Wu, Chen-Jiang; Wang, Qing; Li, Hai; Wang, Xiao-Ning; Liu, Xi-Sheng; Shi, Hai-Bin; Zhang, Yu-Dong

2015-10-01

To investigate diagnostic efficiency of DWI using entire-tumor histogram analysis in differentiating the low-grade (LG) prostate cancer (PCa) from intermediate-high-grade (HG) PCa in comparison with conventional ROI-based measurement. DW images (b of 0-1400 s/mm(2)) from 126 pathology-confirmed PCa (diameter >0.5 cm) in 110 patients were retrospectively collected and processed by mono-exponential model. The measurement of tumor apparent diffusion coefficients (ADCs) was performed with using histogram-based and ROI-based approach, respectively. The diagnostic ability of ADCs from two methods for differentiating LG-PCa (Gleason score, GS ≤ 6) from HG-PCa (GS > 6) was determined by ROC regression, and compared by McNemar's test. There were 49 LG-tumor and 77 HG-tumor at pathologic findings. Histogram-based ADCs (mean, median, 10th and 90th) and ROI-based ADCs (mean) showed dominant relationships with ordinal GS of Pca (ρ = -0.225 to -0.406, p < 0.05). All above imaging indices reflected significant difference between LG-PCa and HG-PCa (all p values <0.01). Histogram 10th ADCs had dominantly high Az (0.738), Youden index (0.415), and positive likelihood ratio (LR+, 2.45) in stratifying tumor GS against mean, median and 90th ADCs, and ROI-based ADCs. Histogram mean, median, and 10th ADCs showed higher specificity (65.3%-74.1% vs. 44.9%, p < 0.01), but lower sensitivity (57.1%-71.3% vs. 84.4%, p < 0.05) than ROI-based ADCs in differentiating LG-PCa from HG-PCa. DWI-associated histogram analysis had higher specificity, Az, Youden index, and LR+ for differentiation of PCa Gleason grade than ROI-based approach.

Performance comparisons between PCA-EA-LBG and PCA-LBG-EA approaches in VQ codebook generation for image compression

NASA Astrophysics Data System (ADS)

Tsai, Jinn-Tsong; Chou, Ping-Yi; Chou, Jyh-Horng

2015-11-01

The aim of this study is to generate vector quantisation (VQ) codebooks by integrating principle component analysis (PCA) algorithm, Linde-Buzo-Gray (LBG) algorithm, and evolutionary algorithms (EAs). The EAs include genetic algorithm (GA), particle swarm optimisation (PSO), honey bee mating optimisation (HBMO), and firefly algorithm (FF). The study is to provide performance comparisons between PCA-EA-LBG and PCA-LBG-EA approaches. The PCA-EA-LBG approaches contain PCA-GA-LBG, PCA-PSO-LBG, PCA-HBMO-LBG, and PCA-FF-LBG, while the PCA-LBG-EA approaches contain PCA-LBG, PCA-LBG-GA, PCA-LBG-PSO, PCA-LBG-HBMO, and PCA-LBG-FF. All training vectors of test images are grouped according to PCA. The PCA-EA-LBG used the vectors grouped by PCA as initial individuals, and the best solution gained by the EAs was given for LBG to discover a codebook. The PCA-LBG approach is to use the PCA to select vectors as initial individuals for LBG to find a codebook. The PCA-LBG-EA used the final result of PCA-LBG as an initial individual for EAs to find a codebook. The search schemes in PCA-EA-LBG first used global search and then applied local search skill, while in PCA-LBG-EA first used local search and then employed global search skill. The results verify that the PCA-EA-LBG indeed gain superior results compared to the PCA-LBG-EA, because the PCA-EA-LBG explores a global area to find a solution, and then exploits a better one from the local area of the solution. Furthermore the proposed PCA-EA-LBG approaches in designing VQ codebooks outperform existing approaches shown in the literature.

Machine learning-based analysis of MR radiomics can help to improve the diagnostic performance of PI-RADS v2 in clinically relevant prostate cancer.

PubMed

Wang, Jing; Wu, Chen-Jiang; Bao, Mei-Ling; Zhang, Jing; Wang, Xiao-Ning; Zhang, Yu-Dong

2017-10-01

To investigate whether machine learning-based analysis of MR radiomics can help improve the performance PI-RADS v2 in clinically relevant prostate cancer (PCa). This IRB-approved study included 54 patients with PCa undergoing multi-parametric (mp) MRI before prostatectomy. Imaging analysis was performed on 54 tumours, 47 normal peripheral (PZ) and 48 normal transitional (TZ) zone based on histological-radiological correlation. Mp-MRI was scored via PI-RADS, and quantified by measuring radiomic features. Predictive model was developed using a novel support vector machine trained with: (i) radiomics, (ii) PI-RADS scores, (iii) radiomics and PI-RADS scores. Paired comparison was made via ROC analysis. For PCa versus normal TZ, the model trained with radiomics had a significantly higher area under the ROC curve (Az) (0.955 [95% CI 0.923-0.976]) than PI-RADS (Az: 0.878 [0.834-0.914], p < 0.001). The Az between them was insignificant for PCa versus PZ (0.972 [0.945-0.988] vs. 0.940 [0.905-0.965], p = 0.097). When radiomics was added, performance of PI-RADS was significantly improved for PCa versus PZ (Az: 0.983 [0.960-0.995]) and PCa versus TZ (Az: 0.968 [0.940-0.985]). Machine learning analysis of MR radiomics can help improve the performance of PI-RADS in clinically relevant PCa. • Machine-based analysis of MR radiomics outperformed in TZ cancer against PI-RADS. • Adding MR radiomics significantly improved the performance of PI-RADS. • DKI-derived Dapp and Kapp were two strong markers for the diagnosis of PCa.

Applying robust variant of Principal Component Analysis as a damage detector in the presence of outliers

NASA Astrophysics Data System (ADS)

Gharibnezhad, Fahit; Mujica, Luis E.; Rodellar, José

2015-01-01

Using Principal Component Analysis (PCA) for Structural Health Monitoring (SHM) has received considerable attention over the past few years. PCA has been used not only as a direct method to identify, classify and localize damages but also as a significant primary step for other methods. Despite several positive specifications that PCA conveys, it is very sensitive to outliers. Outliers are anomalous observations that can affect the variance and the covariance as vital parts of PCA method. Therefore, the results based on PCA in the presence of outliers are not fully satisfactory. As a main contribution, this work suggests the use of robust variant of PCA not sensitive to outliers, as an effective way to deal with this problem in SHM field. In addition, the robust PCA is compared with the classical PCA in the sense of detecting probable damages. The comparison between the results shows that robust PCA can distinguish the damages much better than using classical one, and even in many cases allows the detection where classic PCA is not able to discern between damaged and non-damaged structures. Moreover, different types of robust PCA are compared with each other as well as with classical counterpart in the term of damage detection. All the results are obtained through experiments with an aircraft turbine blade using piezoelectric transducers as sensors and actuators and adding simulated damages.

Demographic, socioeconomic, and behavioral factors affecting patterns of tooth decay in the permanent dentition: Principal components and factor analyses

PubMed Central

Shaffer, John R.; Polk, Deborah E.; Feingold, Eleanor; Wang, Xiaojing; Cuenco, Karen T.; Weeks, Daniel E.; DeSensi, Rebecca S.; Weyant, Robert J.; Crout, Richard; McNeil, Daniel W.; Marazita, Mary L.

2012-01-01

Objectives Dental caries of the permanent dentition is a multi-factorial disease resulting from the complex interplay of endogenous and environmental risk factors. The disease is not easily quantified due to the innumerable possible combinations of carious lesions across individual tooth surfaces of the permanent dentition. Global measures of decay, such as the DMFS index (which was developed for surveillance applications), may not be optimal for studying the epidemiology of dental caries because they ignore the distinct patterns of decay across the dentition. We hypothesize that specific risk factors may manifest their effects on specific tooth surfaces leading to patterns of decay that can be identified and studied. In this study we utilized two statistical methods of extracting patterns of decay from surface-level caries data in order to create novel phenotypes with which to study the risk factors affecting dental caries. Methods Intra-oral dental examinations were performed on 1,068 participants aged 18 to 75 years to assess dental caries. The 128 tooth surfaces of the permanent dentition were scored as carious or not and used as input for principal components analysis (PCA) and factor analysis (FA), two methods of identifying underlying patterns without a priori knowledge of the patterns. Demographic (age, sex, birth year, race/ethnicity, and educational attainment), anthropometric (height, body mass index, waist circumference), endogenous (saliva flow), and environmental (tooth brushing frequency, home water source, and home water fluoride) risk factors were tested for association with the caries patterns identified by PCA and FA, as well as DMFS, for comparison. The ten strongest patterns (i.e., those that explain the most variation in the data set) extracted by PCA and FA were considered. Results The three strongest patterns identified by PCA reflected (i) global extent of decay (i.e., comparable to DMFS index), (ii) pit and fissure surface caries, and (iii) smooth surface caries, respectively. The two strongest patterns identified by FA corresponded to (i) pit and fissure surface caries and (ii) maxillary incisor caries. Age and birth year were significantly associated with several patterns of decay, including global decay/DMFS index. Sex, race, educational attainment, and tooth brushing were each associated with specific patterns of decay, but not with global decay/DMFS index. Conclusions Taken together, these results support the notion that caries experience is separable into patterns attributable to distinct risk factors. This study demonstrates the utility of such novel caries patterns as new outcomes for exploring the complex, multifactorial nature of dental caries. PMID:23106439

Demographic, socioeconomic, and behavioral factors affecting patterns of tooth decay in the permanent dentition: principal components and factor analyses.

PubMed

Shaffer, John R; Polk, Deborah E; Feingold, Eleanor; Wang, Xiaojing; Cuenco, Karen T; Weeks, Daniel E; DeSensi, Rebecca S; Weyant, Robert J; Crout, Richard; McNeil, Daniel W; Marazita, Mary L

2013-08-01

Dental caries of the permanent dentition is a multifactorial disease resulting from the complex interplay of endogenous and environmental risk factors. The disease is not easily quantitated due to the innumerable possible combinations of carious lesions across individual tooth surfaces of the permanent dentition. Global measures of decay, such as the DMFS index (which was developed for surveillance applications), may not be optimal for studying the epidemiology of dental caries because they ignore the distinct patterns of decay across the dentition. We hypothesize that specific risk factors may manifest their effects on specific tooth surfaces leading to patterns of decay that can be identified and studied. In this study, we utilized two statistical methods of extracting patterns of decay from surface-level caries data to create novel phenotypes with which to study the risk factors affecting dental caries. Intra-oral dental examinations were performed on 1068 participants aged 18-75 years to assess dental caries. The 128 tooth surfaces of the permanent dentition were scored as carious or not and used as input for principal components analysis (PCA) and factor analysis (FA), two methods of identifying underlying patterns without a priori knowledge of the patterns. Demographic (age, sex, birth year, race/ethnicity, and educational attainment), anthropometric (height, body mass index, waist circumference), endogenous (saliva flow), and environmental (tooth brushing frequency, home water source, and home water fluoride) risk factors were tested for association with the caries patterns identified by PCA and FA, as well as DMFS, for comparison. The ten strongest patterns (i.e. those that explain the most variation in the data set) extracted by PCA and FA were considered. The three strongest patterns identified by PCA reflected (i) global extent of decay (i.e. comparable to DMFS index), (ii) pit and fissure surface caries and (iii) smooth surface caries, respectively. The two strongest patterns identified by FA corresponded to (i) pit and fissure surface caries and (ii) maxillary incisor caries. Age and birth year were significantly associated with several patterns of decay, including global decay/DMFS index. Sex, race, educational attainment, and tooth brushing were each associated with specific patterns of decay, but not with global decay/DMFS index. Taken together, these results support the notion that caries experience is separable into patterns attributable to distinct risk factors. This study demonstrates the utility of such novel caries patterns as new outcomes for exploring the complex, multifactorial nature of dental caries. © 2012 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Monoamine oxidase A mediates prostate tumorigenesis and cancer metastasis

PubMed Central

Wu, Jason Boyang; Shao, Chen; Li, Xiangyan; Li, Qinlong; Hu, Peizhen; Shi, Changhong; Li, Yang; Chen, Yi-Ting; Yin, Fei; Liao, Chun-Peng; Stiles, Bangyan L.; Zhau, Haiyen E.; Shih, Jean C.; Chung, Leland W.K.

2014-01-01

Tumors from patients with high-grade aggressive prostate cancer (PCa) exhibit increased expression of monoamine oxidase A (MAOA), a mitochondrial enzyme that degrades monoamine neurotransmitters and dietary amines. Despite the association between MAOA and aggressive PCa, it is unclear how MAOA promotes PCa progression. Here, we found that MAOA functions to induce epithelial-to-mesenchymal transition (EMT) and stabilize the transcription factor HIF1α, which mediates hypoxia through an elevation of ROS, thus enhancing growth, invasiveness, and metastasis of PCa cells. Knockdown and overexpression of MAOA in human PCa cell lines indicated that MAOA induces EMT through activation of VEGF and its coreceptor neuropilin-1. MAOA-dependent activation of neuropilin-1 promoted AKT/FOXO1/TWIST1 signaling, allowing FOXO1 binding at the TWIST1 promoter. Importantly, the MAOA-dependent HIF1α/VEGF-A/FOXO1/TWIST1 pathway was activated in high-grade PCa specimens, and knockdown of MAOA reduced or even eliminated prostate tumor growth and metastasis in PCa xenograft mouse models. Pharmacological inhibition of MAOA activity also reduced PCa xenograft growth in mice. Moreover, high MAOA expression in PCa tissues correlated with worse clinical outcomes in PCa patients. These findings collectively characterize the contribution of MAOA in PCa pathogenesis and suggest that MAOA has potential as a therapeutic target in PCa. PMID:24865426

Monoamine oxidase A mediates prostate tumorigenesis and cancer metastasis.

PubMed

Wu, Jason Boyang; Shao, Chen; Li, Xiangyan; Li, Qinlong; Hu, Peizhen; Shi, Changhong; Li, Yang; Chen, Yi-Ting; Yin, Fei; Liao, Chun-Peng; Stiles, Bangyan L; Zhau, Haiyen E; Shih, Jean C; Chung, Leland W K

2014-07-01

Tumors from patients with high-grade aggressive prostate cancer (PCa) exhibit increased expression of monoamine oxidase A (MAOA), a mitochondrial enzyme that degrades monoamine neurotransmitters and dietary amines. Despite the association between MAOA and aggressive PCa, it is unclear how MAOA promotes PCa progression. Here, we found that MAOA functions to induce epithelial-to-mesenchymal transition (EMT) and stabilize the transcription factor HIF1α, which mediates hypoxia through an elevation of ROS, thus enhancing growth, invasiveness, and metastasis of PCa cells. Knockdown and overexpression of MAOA in human PCa cell lines indicated that MAOA induces EMT through activation of VEGF and its coreceptor neuropilin-1. MAOA-dependent activation of neuropilin-1 promoted AKT/FOXO1/TWIST1 signaling, allowing FOXO1 binding at the TWIST1 promoter. Importantly, the MAOA-dependent HIF1α/VEGF-A/FOXO1/TWIST1 pathway was activated in high-grade PCa specimens, and knockdown of MAOA reduced or even eliminated prostate tumor growth and metastasis in PCa xenograft mouse models. Pharmacological inhibition of MAOA activity also reduced PCa xenograft growth in mice. Moreover, high MAOA expression in PCa tissues correlated with worse clinical outcomes in PCa patients. These findings collectively characterize the contribution of MAOA in PCa pathogenesis and suggest that MAOA has potential as a therapeutic target in PCa.

CXCR6 induces prostate cancer progression by the AKT/mammalian target of rapamycin signaling pathway.

PubMed

Wang, Jianhua; Lu, Yi; Wang, Jingchen; Koch, Alisa E; Zhang, Jian; Taichman, Russell S

2008-12-15

Previous studies show that the chemokine CXCL16 and its receptor CXCR6 are likely to contribute to prostate cancer (PCa). In this investigation, the role of the CXCR6 receptor in PCa was further explored. CXCR6 protein expression was examined using high-density tissue microarrays and immunohistochemistry. Expression of CXCR6 showed strong epithelial staining that correlated with Gleason score. In vitro and in vivo studies in PCa cell lines suggested that alterations in CXCR6 expression were associated with invasive activities and tumor growth. In addition, CXCR6 expression was able to regulate expression of the proangiogenic factors interleukin (IL)-8 or vascular endothelial growth factor (VEGF), which are likely to participate in the regulation of tumor angiogenesis. Finally, we found that CXCL16 signaling induced the activation of Akt, p70S6K, and eukaryotic initiation factor 4E binding protein 1 included in mammalian target of rapamycin (mTOR) pathways, which are located downstream of Akt. Furthermore, rapamycin not only drastically inhibited CXCL16-induced PCa cell invasion and growth but reduced secretion of IL-8 or VEGF levels and inhibited expression of other CXCR6 targets including CD44 and matrix metalloproteinase 3 in PCa cells. Together, our data shows for the first time that the CXCR6/AKT/mTOR pathway plays a central role in the development of PCa. Blocking the CXCR6/AKT/mTOR signaling pathway may prove beneficial to prevent metastasis and provide a more effective therapeutic strategy for PCa.

Using Serological Proteome Analysis to Identify Serum Anti-Nucleophosmin 1 Autoantibody as a Potential Biomarker in European-American and African-American Patients With Prostate Cancer.

PubMed

Dai, Liping; Li, Jitian; Xing, Mengtao; Sanchez, Tino W; Casiano, Carlos A; Zhang, Jian-Ying

2016-11-01

The prostate-specific antigen (PSA) testing has been widely implemented for the early detection and management of prostate cancer (PCa). However, the lack of specificity has led to overdiagnosis, resulting in many possibly unnecessary biopsies and overtreatment. Therefore, novel serological biomarkers with high sensitivity and specificity are of vital importance needed to complement PSA testing in the early diagnosis and effective management of PCa. This is particularly critical in the context of PCa health disparities, where early detection and management could help reduce the disproportionately high PCa mortality observed in African-American men. Previous studies have demonstrated that sera from patients with PCa contain autoantibodies that react with tumor-associated antigens (TAAs). The serological proteome analysis (SERPA) approach was used to identify tumor-associated antigens (TAAs) of PCa. In evaluation study, the level of anti-NPM1 antibody was examined in sera from test cohort, validation cohort, as well as European-American (EA) and African-American (AA) men with PCa by using immunoassay. Nucleophosmin 1 (NPM1) as a 33 kDa TAA in PCa was identified and characterized by SERPA approach. Anti-NPM1 antibody level in PCa was higher than in benign prostatic hyperplasia (BPH) patients and healthy individuals. Receiver operating characteristic (ROC) curve analysis showed similar high diagnostic value for PCa in the test cohort (area under the curve (AUC):0.860) and validation cohort (AUC: 0.822) to differentiate from normal individuals and BPH. Interestingly, AUC values were significantly higher for AA PCa patients. When considering concurrent serum measurements of anti-NPM1 antibody and PSA, 97.1% PCa patients at early stage were identified correctly, while 69.2% BPH patients who had elevated PSA levels were found to be anti-NPM1 negative. Additionally, anti-NPM1 antibody levels in PCa patients at early stage significantly increased after surgery treatment. This intriguing data suggested that NPM1 can elicit autoantibody response in PCa and might be a potential biomarker for the immunodiagnosis and prognosis of PCa, and for supplementing PSA testing in distinguishing PCa from BPH. Prostate 76:1375-1386, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Prostate Cancer Predictive Simulation Modelling, Assessing the Risk Technique (PCP-SMART): Introduction and Initial Clinical Efficacy Evaluation Data Presentation of a Simple Novel Mathematical Simulation Modelling Method, Devised to Predict the Outcome of Prostate Biopsy on an Individual Basis.

PubMed

Spyropoulos, Evangelos; Kotsiris, Dimitrios; Spyropoulos, Katherine; Panagopoulos, Aggelos; Galanakis, Ioannis; Mavrikos, Stamatios

2017-02-01

We developed a mathematical "prostate cancer (PCa) conditions simulating" predictive model (PCP-SMART), from which we derived a novel PCa predictor (prostate cancer risk determinator [PCRD] index) and a PCa risk equation. We used these to estimate the probability of finding PCa on prostate biopsy, on an individual basis. A total of 371 men who had undergone transrectal ultrasound-guided prostate biopsy were enrolled in the present study. Given that PCa risk relates to the total prostate-specific antigen (tPSA) level, age, prostate volume, free PSA (fPSA), fPSA/tPSA ratio, and PSA density and that tPSA ≥ 50 ng/mL has a 98.5% positive predictive value for a PCa diagnosis, we hypothesized that correlating 2 variables composed of 3 ratios (1, tPSA/age; 2, tPSA/prostate volume; and 3, fPSA/tPSA; 1 variable including the patient's tPSA and the other, a tPSA value of 50 ng/mL) could operate as a PCa conditions imitating/simulating model. Linear regression analysis was used to derive the coefficient of determination (R 2 ), termed the PCRD index. To estimate the PCRD index's predictive validity, we used the χ 2 test, multiple logistic regression analysis with PCa risk equation formation, calculation of test performance characteristics, and area under the receiver operating characteristic curve analysis using SPSS, version 22 (P < .05). The biopsy findings were positive for PCa in 167 patients (45.1%) and negative in 164 (44.2%). The PCRD index was positively signed in 89.82% positive PCa cases and negative in 91.46% negative PCa cases (χ 2 test; P < .001; relative risk, 8.98). The sensitivity was 89.8%, specificity was 91.5%, positive predictive value was 91.5%, negative predictive value was 89.8%, positive likelihood ratio was 10.5, negative likelihood ratio was 0.11, and accuracy was 90.6%. Multiple logistic regression revealed the PCRD index as an independent PCa predictor, and the formulated risk equation was 91% accurate in predicting the probability of finding PCa. On the receiver operating characteristic analysis, the PCRD index (area under the curve, 0.926) significantly (P < .001) outperformed other, established PCa predictors. The PCRD index effectively predicted the prostate biopsy outcome, correctly identifying 9 of 10 men who were eventually diagnosed with PCa and correctly ruling out PCa for 9 of 10 men who did not have PCa. Its predictive power significantly outperformed established PCa predictors, and the formulated risk equation accurately calculated the probability of finding cancer on biopsy, on an individual patient basis. Copyright © 2016 Elsevier Inc. All rights reserved.

Examination of polymorphic glutathione S-transferase (GST) genes, tobacco smoking and prostate cancer risk among Men of African Descent: A case-control study

PubMed Central

2009-01-01

Background Polymorphisms in glutathione S-transferase (GST) genes may influence response to oxidative stress and modify prostate cancer (PCA) susceptibility. These enzymes generally detoxify endogenous and exogenous agents, but also participate in the activation and inactivation of oxidative metabolites that may contribute to PCA development. Genetic variations within selected GST genes may influence PCA risk following exposure to carcinogen compounds found in cigarette smoke and decreased the ability to detoxify them. Thus, we evaluated the effects of polymorphic GSTs (M1, T1, and P1) alone and combined with cigarette smoking on PCA susceptibility. Methods In order to evaluate the effects of GST polymorphisms in relation to PCA risk, we used TaqMan allelic discrimination assays along with a multi-faceted statistical strategy involving conventional and advanced statistical methodologies (e.g., Multifactor Dimensionality Reduction and Interaction Graphs). Genetic profiles collected from 873 men of African-descent (208 cases and 665 controls) were utilized to systematically evaluate the single and joint modifying effects of GSTM1 and GSTT1 gene deletions, GSTP1 105 Val and cigarette smoking on PCA risk. Results We observed a moderately significant association between risk among men possessing at least one variant GSTP1 105 Val allele (OR = 1.56; 95%CI = 0.95-2.58; p = 0.049), which was confirmed by MDR permutation testing (p = 0.001). We did not observe any significant single gene effects among GSTM1 (OR = 1.08; 95%CI = 0.65-1.82; p = 0.718) and GSTT1 (OR = 1.15; 95%CI = 0.66-2.02; p = 0.622) on PCA risk among all subjects. Although the GSTM1-GSTP1 pairwise combination was selected as the best two factor LR and MDR models (p = 0.01), assessment of the hierarchical entropy graph suggested that the observed synergistic effect was primarily driven by the GSTP1 Val marker. Notably, the GSTM1-GSTP1 axis did not provide additional information gain when compared to either loci alone based on a hierarchical entropy algorithm and graph. Smoking status did not significantly modify the relationship between the GST SNPs and PCA. Conclusion A moderately significant association was observed between PCA risk and men possessing at least one variant GSTP1 105 Val allele (p = 0.049) among men of African descent. We also observed a 2.1-fold increase in PCA risk associated with men possessing the GSTP1 (Val/Val) and GSTM1 (*1/*1 + *1/*0) alleles. MDR analysis validated these findings; detecting GSTP1 105 Val (p = 0.001) as the best single factor for predicting PCA risk. Our findings emphasize the importance of utilizing a combination of traditional and advanced statistical tools to identify and validate single gene and multi-locus interactions in relation to cancer susceptibility. PMID:19917083

The Northern Norway Mother-and-Child Contaminant Cohort (MISA) Study: PCA analyses of environmental contaminants in maternal sera and dietary intake in early pregnancy.

PubMed

Veyhe, Anna Sofía; Hofoss, Dag; Hansen, Solrunn; Thomassen, Yngvar; Sandanger, Torkjel M; Odland, Jon Øyvind; Nieboer, Evert

2015-03-01

Although predictors of contaminants in serum or whole blood are usually examined by chemical groups (e.g., POPs, toxic and/or essential elements; dietary sources), principal component analysis (PCA) permits consideration of both individual substances and combined variables. Our study had two primary objectives: (i) Characterize the sources and predictors of a suite of eight PCBs, four organochlorine (OC) pesticides, five essential and five toxic elements in serum and/or whole blood of pregnant women recruited as part of the Mother-and-Child Contaminant Cohort Study conducted in Northern Norway (The MISA study); and (ii) determine the influence of personal and social characteristics on both dietary and contaminant factors. Recruitment and sampling started in May 2007 and continued for the next 31 months until December 2009. Blood/serum samples were collected during the 2nd trimester (mean: 18.2 weeks, range 9.0-36.0). A validated questionnaire was administered to obtain personal information. The samples were analysed by established laboratories employing verified methods and reference standards. PCA involved Varimax rotation, and significant predictors (p≤0.05) in linear regression models were included in the multivariable linear regression analysis. When considering all the contaminants, three prominent PCA axes stood out with prominent loadings of: all POPs; arsenic, selenium and mercury; and cadmium and lead. Respectively, in the multivariate models the following were predictors: maternal age, parity and consumption of freshwater fish and land-based wild animals; marine fish; cigarette smoking, dietary PCA axes reflecting consumption of grains and cereals, and food items involving hunting. PCA of only the POPs separated them into two axes that, in terms of recently published findings, could be understood to reflect longitudinal trends and their relative contributions to summed POPs. The linear combinations of variables generated by PCA identified prominent dietary sources of OC groups and of prominent toxic elements and highlighted the importance of maternal characteristics. Copyright © 2014 Elsevier GmbH. All rights reserved.

Androgen receptor (AR) cistrome in prostate differentiation and cancer progression.

PubMed

Wang, Fengtian; Koul, Hari K

2017-01-01

Despite the progress in development of better AR-targeted therapies for prostate cancer (PCa), there is no curative therapy for castration-resistant prostate cancer (CRPC). Therapeutic resistance in PCa can be characterized in two broad categories of AR therapy resistance: the first and most prevalent one involves restoration of AR activity despite AR targeted therapy, and the second one involves tumor progression despite blockade of AR activity. As such AR remains the most attractive drug target for CRPC. Despite its oncogenic role, AR signaling also contributes to the maturation and differentiation of prostate luminal cells during development. Recent evidence suggests that AR cistrome is altered in advanced PCa. Alteration in AR may result from AR amplification, alternative splicing, mutations, post-translational modification of AR, and altered expression of AR co-factors. We reasoned that such alterations would result in the transcription of disparate AR target genes and as such may contribute to the emergence of castration-resistance. In the present study, we evaluated the expression of genes associated with canonical or non-canonical AR cistrome in relationship with PCa progression and prostate development by analyzing publicly available datasets. We discovered a transcription switch from canonical AR cistrome target genes to the non-canonical AR cistrome target genes during PCa progression. Using Gene Set Enrichment Analysis (GSEA), we discovered that canonical AR cistrome target genes are enriched in indolent PCa patients and the loss of canonical AR cistrome is associated with tumor metastasis and poor clinical outcome. Analysis of the datasets involving prostate development, revealed that canonical AR cistrome target genes are significantly enriched in prostate luminal cells and can distinguish luminal cells from basal cells, suggesting a pivotal role for canonical AR cistrome driven genes in prostate development. These data suggest that the expression of canonical AR cistrome related genes play an important role in maintaining the prostate luminal cell identity and might restrict the lineage plasticity observed in lethal PCa. Understanding the molecular mechanisms that dictate AR cistrome may lead to development of new therapeutic strategies aimed at restoring canonical AR cistrome, rewiring the oncogenic AR signaling and overcome resistance to AR targeted therapies.

GO-PCA: An Unsupervised Method to Explore Gene Expression Data Using Prior Knowledge

PubMed Central

Wagner, Florian

2015-01-01

Method Genome-wide expression profiling is a widely used approach for characterizing heterogeneous populations of cells, tissues, biopsies, or other biological specimen. The exploratory analysis of such data typically relies on generic unsupervised methods, e.g. principal component analysis (PCA) or hierarchical clustering. However, generic methods fail to exploit prior knowledge about the molecular functions of genes. Here, I introduce GO-PCA, an unsupervised method that combines PCA with nonparametric GO enrichment analysis, in order to systematically search for sets of genes that are both strongly correlated and closely functionally related. These gene sets are then used to automatically generate expression signatures with functional labels, which collectively aim to provide a readily interpretable representation of biologically relevant similarities and differences. The robustness of the results obtained can be assessed by bootstrapping. Results I first applied GO-PCA to datasets containing diverse hematopoietic cell types from human and mouse, respectively. In both cases, GO-PCA generated a small number of signatures that represented the majority of lineages present, and whose labels reflected their respective biological characteristics. I then applied GO-PCA to human glioblastoma (GBM) data, and recovered signatures associated with four out of five previously defined GBM subtypes. My results demonstrate that GO-PCA is a powerful and versatile exploratory method that reduces an expression matrix containing thousands of genes to a much smaller set of interpretable signatures. In this way, GO-PCA aims to facilitate hypothesis generation, design of further analyses, and functional comparisons across datasets. PMID:26575370

GO-PCA: An Unsupervised Method to Explore Gene Expression Data Using Prior Knowledge.

PubMed

Wagner, Florian

2015-01-01

Genome-wide expression profiling is a widely used approach for characterizing heterogeneous populations of cells, tissues, biopsies, or other biological specimen. The exploratory analysis of such data typically relies on generic unsupervised methods, e.g. principal component analysis (PCA) or hierarchical clustering. However, generic methods fail to exploit prior knowledge about the molecular functions of genes. Here, I introduce GO-PCA, an unsupervised method that combines PCA with nonparametric GO enrichment analysis, in order to systematically search for sets of genes that are both strongly correlated and closely functionally related. These gene sets are then used to automatically generate expression signatures with functional labels, which collectively aim to provide a readily interpretable representation of biologically relevant similarities and differences. The robustness of the results obtained can be assessed by bootstrapping. I first applied GO-PCA to datasets containing diverse hematopoietic cell types from human and mouse, respectively. In both cases, GO-PCA generated a small number of signatures that represented the majority of lineages present, and whose labels reflected their respective biological characteristics. I then applied GO-PCA to human glioblastoma (GBM) data, and recovered signatures associated with four out of five previously defined GBM subtypes. My results demonstrate that GO-PCA is a powerful and versatile exploratory method that reduces an expression matrix containing thousands of genes to a much smaller set of interpretable signatures. In this way, GO-PCA aims to facilitate hypothesis generation, design of further analyses, and functional comparisons across datasets.

Incorporating biological information in sparse principal component analysis with application to genomic data.

PubMed

Li, Ziyi; Safo, Sandra E; Long, Qi

2017-07-11

Sparse principal component analysis (PCA) is a popular tool for dimensionality reduction, pattern recognition, and visualization of high dimensional data. It has been recognized that complex biological mechanisms occur through concerted relationships of multiple genes working in networks that are often represented by graphs. Recent work has shown that incorporating such biological information improves feature selection and prediction performance in regression analysis, but there has been limited work on extending this approach to PCA. In this article, we propose two new sparse PCA methods called Fused and Grouped sparse PCA that enable incorporation of prior biological information in variable selection. Our simulation studies suggest that, compared to existing sparse PCA methods, the proposed methods achieve higher sensitivity and specificity when the graph structure is correctly specified, and are fairly robust to misspecified graph structures. Application to a glioblastoma gene expression dataset identified pathways that are suggested in the literature to be related with glioblastoma. The proposed sparse PCA methods Fused and Grouped sparse PCA can effectively incorporate prior biological information in variable selection, leading to improved feature selection and more interpretable principal component loadings and potentially providing insights on molecular underpinnings of complex diseases.

Exploratory factor analysis of the 12-item Functional Assessment of Chronic Illness Therapy-Spiritual Well-Being Scale in people newly diagnosed with advanced cancer.

PubMed

Bai, Mei; Dixon, Jane K

2014-01-01

The purpose of this study was to reexamine the factor pattern of the 12-item Functional Assessment of Chronic Illness Therapy-Spiritual Well-Being Scale (FACIT-Sp-12) using exploratory factor analysis in people newly diagnosed with advanced cancer. Principal components analysis (PCA) and 3 common factor analysis methods were used to explore the factor pattern of the FACIT-Sp-12. Factorial validity was assessed in association with quality of life (QOL). Principal factor analysis (PFA), iterative PFA, and maximum likelihood suggested retrieving 3 factors: Peace, Meaning, and Faith. Both Peace and Meaning positively related to QOL, whereas only Peace uniquely contributed to QOL. This study supported the 3-factor model of the FACIT-Sp-12. Suggestions for revision of items and further validation of the identified factor pattern were provided.

The Effect of Phenazine-1-Carboxylic Acid on Mycelial Growth of Botrytis cinerea Produced by Pseudomonas aeruginosa LV Strain

PubMed Central

Simionato, Ane S.; Navarro, Miguel O. P.; de Jesus, Maria L. A.; Barazetti, André R.; da Silva, Caroline S.; Simões, Glenda C.; Balbi-Peña, Maria I.; de Mello, João C. P.; Panagio, Luciano A.; de Almeida, Ricardo S. C.; Andrade, Galdino; de Oliveira, Admilton G.

2017-01-01

One of the most important postharvest plant pathogens that affect strawberries, grapes and tomatoes is Botrytis cinerea, known as gray mold. The fungus remains in latent form until spore germination conditions are good, making infection control difficult, causing great losses in the whole production chain. This study aimed to purify and identify phenazine-1-carboxylic acid (PCA) produced by the Pseudomonas aeruginosa LV strain and to determine its antifungal activity against B. cinerea. The compounds produced were extracted with dichloromethane and passed through a chromatographic process. The purity level of PCA was determined by reversed-phase high-performance liquid chromatography semi-preparative. The structure of PCA was confirmed by nuclear magnetic resonance and electrospray ionization mass spectrometry. Antifungal activity was determined by the dry paper disk and minimum inhibitory concentration (MIC) methods and identified by scanning electron microscopy and confocal microscopy. The results showed that PCA inhibited mycelial growth, where MIC was 25 μg mL-1. Microscopic analysis revealed a reduction in exopolysaccharide (EPS) formation, showing distorted and damaged hyphae of B. cinerea. The results suggested that PCA has a high potential in the control of B. cinerea and inhibition of EPS (important virulence factor). This natural compound is a potential alternative to postharvest control of gray mold disease. PMID:28659907

Duke Workshop on High-Dimensional Data Sensing and Analysis

DTIC Science & Technology

2015-05-06

Bayesian sparse factor analysis formulation of Chen et al . ( 2011 ) this work develops multi-label PCA (MLPCA), a generative dimension reduction...version of this problem was recently treated by Banerjee et al . [1], Ravikumar et al . [2], Kolar and Xing [3], and Ho ̈fling and Tibshirani [4]. As...Not applicable. Final Report Duke Workshop on High-Dimensional Data Sensing and Analysis Workshop Dates: July 26-28, 2011

Optimization of critical medium components using response surface methodology for phenazine-1-carboxylic acid production by Pseudomonas sp. M-18Q.

PubMed

Yuan, Li-Li; Li, Ya-Qian; Wang, Yi; Zhang, Xue-Hong; Xu, Yu-Quan

2008-03-01

The optimal flask-shaking batch fermentation medium for phenazine-1-carboxylic acid (PCA) production by Pseudomonas sp. M-18Q, a qscR chromosomal inactivated mutant of the strain M18 was studied using statistical experimental design and analysis. The Plackett-Burman design (PBD) was used to evaluate the effects of eight medium components on the production of PCA, which showed that glucose and soytone were the most significant ingredients (P<0.05). The steepest ascent experiment was adopted to determine the optimal region of the medium composition. The optimum composition of the fermentation medium for maximum PCA yield, as determined on the basis of a five-level two-factor central composite design (CCD), was obtained by response surface methodology (RSM). The high correlation between the predicted and observed values indicated the validity of the model. A maximum PCA yield of 1240 mg/l was obtained at 17.81 g/l glucose and 11.47 g/l soytone, and the production was increased by 65.3% compared with that using the original medium, which was at 750 mg/l.

Nuclear C-MYC expression level is associated with disease progression and potentially predictive of two year overall survival in prostate cancer.

PubMed

Zeng, Wen; Sun, Hanying; Meng, Fankai; Liu, Zeming; Xiong, Jing; Zhou, Sheng; Li, Fan; Hu, Jia; Hu, Zhiquan; Liu, Zheng

2015-01-01

Upregulation of nuclear C-MYC protein has been reported to be an early event in prostate cancer (PCa); however, its clinicopathological and prognostic significance remain controversial. We determined the association of nuclear C-MYC protein expression with clinicopathological parameters, prognosis, ETS-related gene (ERG) expression, and TMPRSS2-ERG status in PCa. Nuclear C-MYC and ERG expression by immunohistochemistry and TMPRSS2-ERG status by triple-color probe fluorescence in situ hybridization assay were determined in 50 hormone-naïve PCa patients and 31 radical prostatectomy specimens. Nuclear C-MYC immunostaining was negative, positive, and strong positive in 27.5%, 32.5%, and 40.0% of cases, respectively. C-MYC immunostaining was significantly associated with clinical T stage (P < 0.001), distant metastasis at the time of diagnosis (P < 0.001) and TMPRSS2-ERG status (P = 0.001) but not with ERG immunostaining (P = 0.818). In the Kaplan-Meier analysis, C-MYC positive cases were found to have worse 2-year OS compared with C-MYC negative cases (P = 0.027). However, in the univariate Cox analysis, only TMPRSS2-ERG status (hazard ratio [HR] 0.189, 95% CI 0.057-0.629; P = 0.007) and distant metastasis (HR 3.545, 95% CI 1.056-11.894; P = 0.040) were significantly associated with 2-year OS. After adjusting for these two factors, TMPRSS2-ERG status still impacted 2-year OS (HR 0.196, 95% CI 0.049-0.778; P = 0.020). Nuclear C-MYC overexpression may be associated with disease progression and potentially predictive of 2-year OS in PCa. This is the first study to demonstrate an association between nuclear C-MYC immunostaining and TMPRSS2-ERG status in PCa.

Improved medical image fusion based on cascaded PCA and shift invariant wavelet transforms.

PubMed

Reena Benjamin, J; Jayasree, T

2018-02-01

In the medical field, radiologists need more informative and high-quality medical images to diagnose diseases. Image fusion plays a vital role in the field of biomedical image analysis. It aims to integrate the complementary information from multimodal images, producing a new composite image which is expected to be more informative for visual perception than any of the individual input images. The main objective of this paper is to improve the information, to preserve the edges and to enhance the quality of the fused image using cascaded principal component analysis (PCA) and shift invariant wavelet transforms. A novel image fusion technique based on cascaded PCA and shift invariant wavelet transforms is proposed in this paper. PCA in spatial domain extracts relevant information from the large dataset based on eigenvalue decomposition, and the wavelet transform operating in the complex domain with shift invariant properties brings out more directional and phase details of the image. The significance of maximum fusion rule applied in dual-tree complex wavelet transform domain enhances the average information and morphological details. The input images of the human brain of two different modalities (MRI and CT) are collected from whole brain atlas data distributed by Harvard University. Both MRI and CT images are fused using cascaded PCA and shift invariant wavelet transform method. The proposed method is evaluated based on three main key factors, namely structure preservation, edge preservation, contrast preservation. The experimental results and comparison with other existing fusion methods show the superior performance of the proposed image fusion framework in terms of visual and quantitative evaluations. In this paper, a complex wavelet-based image fusion has been discussed. The experimental results demonstrate that the proposed method enhances the directional features as well as fine edge details. Also, it reduces the redundant details, artifacts, distortions.

Promoter methylation of the immune checkpoint receptor PD-1 (PDCD1) is an independent prognostic biomarker for biochemical recurrence-free survival in prostate cancer patients following radical prostatectomy

PubMed Central

Goltz, Diane; Gevensleben, Heidrun; Dietrich, Jörn; Ellinger, Jörg; Landsberg, Jennifer; Kristiansen, Glen; Dietrich, Dimo

2016-01-01

ABSTRACT Biomarkers that facilitate the prediction of disease recurrence in prostate cancer (PCa) may enable physicians to personalize treatment for individual patients. In the current study, PD-1 (PDCD1) promoter methylation was assessed in a cohort of 498 PCa patients included in The Cancer Genome Atlas (TCGA) and a second cohort of 300 PCa cases treated at the University Hospital of Bonn. In the TCGA cohort, the PD-1 promoter was significantly hypermethylated in carcinomas versus normal prostatic epithelium (55.5% vs. 38.2%, p < 0.001) and PD-1 methylation (mPD-1) inversely correlated with PD-1 mRNA expression in PCa (Spearman's ρ = −0.415, p < 0.001). In both cohorts, mPD-1 significantly correlated with preoperative prostate specific antigen (PSA). In univariate Cox Proportional Hazard analysis, mPD-1 served as a significant prognostic factor for biochemical recurrence (BCR)-free survival (Hazard ratio: HR = 2.35 [1.35–4.10], p = 0.003, n = 410) in the TCGA cohort. In multivariate analysis, mPD-1 was shown to add significant independent prognostic information adjunct to pathologic tumor category (pT) and Gleason grading group (HR = 2.08 [1.16–3.74], p = 0.014, n = 350). PD-1 promoter methylation analyses could thus potentially aid the identification of patients which might benefit from adjuvant treatment after radical prostatectomy. Moreover, our data suggest an intrinsic role of PD-1 in PCa carcinogenesis and disease progression, which needs to be addressed in future studies. PMID:27853645

Parent–Child Aggression Risk in Expectant Mothers and Fathers: A Multimethod Theoretical Approach

PubMed Central

Smith, Tamika L.; Silvia, Paul J.

2016-01-01

The current investigation evaluated whether cognitive processes characteristic of the Social Information Processing model predicted parent-child aggression (PCA) risk independent of personal vulnerabilities and resiliencies. This study utilized a multimethod approach, including analog tasks, with a diverse sample of 203 primiparous expectant mothers and 151 of their partners. Factors considered in this study included PCA approval attitudes, empathy, reactivity, negative child attributions, compliance expectations, and knowledge of non-physical discipline alternatives; additionally, vulnerabilities included psychopathology symptoms, domestic violence victimization, and substance use, whereas resiliencies included perceived social support, partner relationship satisfaction, and coping efficacy. For both mothers and fathers, findings supported the role of greater approval of PCA attitudes, lower empathy, more overreactivity, more negative attributions, and higher compliance expectations in relation to elevated risk of PCA. Moreover, personal vulnerabilities and resiliencies related to PCA risk for mothers; however, fathers and mothers differed on the nature of these relationships with respect to vulnerabilities as well as aspects of empathy and PCA approval attitudes. Findings provide evidence for commonalities in many of the factors investigated between mothers and fathers with some notable distinctions. Results are discussed in terms of how findings could inform prevention programs. PMID:28082826

Evaluation of seasonal variation of water quality using multivariate statistical analysis and irrigation parameter indices in Ajakanga area, Ibadan, Nigeria

NASA Astrophysics Data System (ADS)

Ganiyu, S. A.; Badmus, B. S.; Olurin, O. T.; Ojekunle, Z. O.

2018-03-01

The variation of groundwater quality across different regions is of great importance in the study of groundwater so as to ascertain the sources of contaminants to available water sources. Geochemical assessment of groundwater samples from hand-dug wells were done within the vicinity of Ajakanga dumpsite, Ibadan, Southwestern, Nigeria, with the aim of assessing their suitability for domestic and irrigation purposes. Ten groundwater samples were collected both in dry and wet seasons for analysis of physicochemical parameters such as: pH, EC, TDS, Na+, K+, Ca2+, Mg2+, HCO3^{ - } Cl-, SO4^{2 - }, NO3^{2 - } principal component analysis (PCA) and cluster analysis (CA) were used to determine probable sources of groundwater contamination. The results of the analyses showed the groundwater samples to be within permissible limits of WHO/NSDWQ, while elevated values of concentrations of most analyzed chemical constituents in water samples were noticed in S1 and S10 due to their nearness to the dumpsite and agricultural overflow, respectively. Groundwater in the study area is of hard, fresh and alkaline nature. There are very strong associations between EC and TDS, HCO3^{ - } and CO3^{2 - } in both seasons. PCA identified five and three major factors accounting for 95.7 and 88.7% of total variation in water quality for dry and wet seasons, respectively. PCA also identified factors influencing water quality as those probably related to mineral dissolution, groundwater-rock interaction, weathering process and anthropogenic activities from the dumpsite. Results of CA show groups based on similar water quality characteristics and on the extent of proximity to the dumpsite. Assessment for irrigation purpose showed that most of the water samples were suitable for agricultural purpose except in a few locations.

miR-188-5p inhibits tumour growth and metastasis in prostate cancer by repressing LAPTM4B expression

PubMed Central

Zhang, Hongtuan; Qi, Shiyong; Zhang, Tao; Wang, Andi; Liu, Ranlu; Guo, Jia; Wang, Yuzhuo; Xu, Yong

2015-01-01

Elucidation of the molecular targets and pathways regulated by the tumour-suppressive miRNAs can shed light on the oncogenic and metastatic processes in prostate cancer (PCa). Using miRNA profiling analysis, we find that miR-188-5p was significantly down-regulated in metastatic PCa. Down-regulation of miR-188-5p is an independent prognostic factor for poor overall and biochemical recurrence-free survival. Restoration of miR-188-5p in PCa cells (PC-3 and LNCaP) significantly suppresses proliferation, migration and invasion in vitro and inhibits tumour growth and metastasis in vivo. We also find overexpression of miR-188-5p in PC-3 cells can significantly enhance the cells' chemosensitivity to adriamycin. LAPTM4B is subsequently identified as a direct target of miR-188-5p in PCa, and is found to be significantly over-expressed in PCa. Knockdown of LAPTM4B phenotypically copies miR-188-5p-induced phenotypes, whereas ectopic expression of LAPTM4B reverses the effects of miR-188-5p. We also find that restoration of miR-188-5p can inhibit the PI3K/AKT signaling pathway via the suppression of LAPTM4B. Taken together, this is the first report unveils that miR-188-5p acts as a tumour suppressor in PCa and may therefore serve as a useful therapeutic target for the development of new anticancer therapy. PMID:25714029

Beliefs about surgery: Development and validation of an instrument to assess cognitive representations about surgery, in the context of a chronic illness.

PubMed

Francis, Jillian J; Wileman, Samantha M; Bekker, Hilary; Barton, Garry R; Ramsay, Craig R

2009-12-01

Within a trial of medical and surgical treatments for gastro-esophageal reflux disease (GORD), involving randomised arms and preference arms, we tested the applicability of the Beliefs about Medicines Questionnaire (BMQ) and developed and tested the validity of a new Beliefs about Surgery Questionnaire (BSQ). Patients with GORD (N = 43) were interviewed to elicit their beliefs about medical and surgical treatments. These contributed to the development of BSQ items. The BMQ and BSQ were completed by trial participants at baseline (randomised trial: N = 325; preference trial: N = 414). Factor analysis and discriminant function analysis were used to assess validity. Principal components analysis (PCA) largely replicated the four-factor BMQ structure. PCA of the combined BMQ/BSQ yielded six factors explaining 54.5% variance. BSQ items loaded onto distinct factors, demonstrating divergence from BMQ. As predicted, BMQ/BSQ scores enabled correct classification of 78.5% of participants to medication and surgery groups in the preference trial (chi(2)(6) = 205.9, p < 0.001) but only 54.5% (no better than chance) in the randomised trial (chi(2)(6) = 9.4, p = 0.154). The BSQ is a valid measure of perceptions about surgical treatments for GORD. With the BMQ, it provides information that may guide patients' choices about treatment. This measure may be applicable to other conditions.

The impact of moderate wine consumption on the risk of developing prostate cancer.

PubMed

Vartolomei, Mihai Dorin; Kimura, Shoji; Ferro, Matteo; Foerster, Beat; Abufaraj, Mohammad; Briganti, Alberto; Karakiewicz, Pierre I; Shariat, Shahrokh F

2018-01-01

To investigate the impact of moderate wine consumption on the risk of prostate cancer (PCa). We focused on the differential effect of moderate consumption of red versus white wine. This study was a meta-analysis that includes data from case-control and cohort studies. A systematic search of Web of Science, Medline/PubMed, and Cochrane library was performed on December 1, 2017. Studies were deemed eligible if they assessed the risk of PCa due to red, white, or any wine using multivariable logistic regression analysis. We performed a formal meta-analysis for the risk of PCa according to moderate wine and wine type consumption (white or red). Heterogeneity between studies was assessed using Cochrane's Q test and I 2 statistics. Publication bias was assessed using Egger's regression test. A total of 930 abstracts and titles were initially identified. After removal of duplicates, reviews, and conference abstracts, 83 full-text original articles were screened. Seventeen studies (611,169 subjects) were included for final evaluation and fulfilled the inclusion criteria. In the case of moderate wine consumption: the pooled risk ratio (RR) for the risk of PCa was 0.98 (95% CI 0.92-1.05, p =0.57) in the multivariable analysis. Moderate white wine consumption increased the risk of PCa with a pooled RR of 1.26 (95% CI 1.10-1.43, p =0.001) in the multi-variable analysis. Meanwhile, moderate red wine consumption had a protective role reducing the risk by 12% (RR 0.88, 95% CI 0.78-0.999, p =0.047) in the multivariable analysis that comprised 222,447 subjects. In this meta-analysis, moderate wine consumption did not impact the risk of PCa. Interestingly, regarding the type of wine, moderate consumption of white wine increased the risk of PCa, whereas moderate consumption of red wine had a protective effect. Further analyses are needed to assess the differential molecular effect of white and red wine conferring their impact on PCa risk.

Q-mode versus R-mode principal component analysis for linear discriminant analysis (LDA)

NASA Astrophysics Data System (ADS)

Lee, Loong Chuen; Liong, Choong-Yeun; Jemain, Abdul Aziz

2017-05-01

Many literature apply Principal Component Analysis (PCA) as either preliminary visualization or variable con-struction methods or both. Focus of PCA can be on the samples (R-mode PCA) or variables (Q-mode PCA). Traditionally, R-mode PCA has been the usual approach to reduce high-dimensionality data before the application of Linear Discriminant Analysis (LDA), to solve classification problems. Output from PCA composed of two new matrices known as loadings and scores matrices. Each matrix can then be used to produce a plot, i.e. loadings plot aids identification of important variables whereas scores plot presents spatial distribution of samples on new axes that are also known as Principal Components (PCs). Fundamentally, the scores matrix always be the input variables for building classification model. A recent paper uses Q-mode PCA but the focus of analysis was not on the variables but instead on the samples. As a result, the authors have exchanged the use of both loadings and scores plots in which clustering of samples was studied using loadings plot whereas scores plot has been used to identify important manifest variables. Therefore, the aim of this study is to statistically validate the proposed practice. Evaluation is based on performance of external error obtained from LDA models according to number of PCs. On top of that, bootstrapping was also conducted to evaluate the external error of each of the LDA models. Results show that LDA models produced by PCs from R-mode PCA give logical performance and the matched external error are also unbiased whereas the ones produced with Q-mode PCA show the opposites. With that, we concluded that PCs produced from Q-mode is not statistically stable and thus should not be applied to problems of classifying samples, but variables. We hope this paper will provide some insights on the disputable issues.

A structural investigation into the compaction behavior of pharmaceutical composites using powder X-ray diffraction and total scattering analysis.

PubMed

Moore, Michael D; Steinbach, Alison M; Buckner, Ira S; Wildfong, Peter L D

2009-11-01

To use advanced powder X-ray diffraction (PXRD) to characterize the structure of anhydrous theophylline following compaction, alone, and as part of a binary mixture with either alpha-lactose monohydrate or microcrystalline cellulose. Compacts formed from (1) pure theophylline and (2) each type of binary mixture were analyzed intact using PXRD. A novel mathematical technique was used to accurately separate multi-component diffraction patterns. The pair distribution function (PDF) of isolated theophylline diffraction data was employed to assess structural differences induced by consolidation and evaluated by principal components analysis (PCA). Changes induced in PXRD patterns by increasing compaction pressure were amplified by the PDF. Simulated data suggest PDF dampening is attributable to molecular deviations from average crystalline position. Samples compacted at different pressures were identified and differentiated using PCA. Samples compacted at common pressures exhibited similar inter-atomic correlations, where excipient concentration factored in the analyses involving lactose. Practical real-space structural analysis of PXRD data by PDF was accomplished for intact, compacted crystalline drug with and without excipient. PCA was used to compare multiple PDFs and successfully differentiated pattern changes consistent with compaction-induced disordering of theophylline as a single component and in the presence of another material.

The factor structure and reliability of the Illness Attitude Scales in a student and a patient sample

PubMed Central

Crössmann, Alexander; Pauli, Paul

2006-01-01

Background The Illness Attitude Scales (IAS), designed by Kellner in 1986, assesses fears, beliefs, and attitudes associated with hypochondriasis and abnormal illness behaviour. However, its factor structure is, especially for translations of the IAS, not sufficiently explored. Thus, the present Study aimed to analyse the factor structure of the IAS in a German student and a patient population using exploratory factor analysis. Methods A mixed student (N = 296) and a mixed patient (N = 130) sample completed the IAS. The data was submitted to principal components analyses (PCA) with subsequent oblique rotations. From identified factor structures, scales were derived and submitted to reliability analyses as well as to a preliminary validity analysis. Results The PCA revealed a four-factor solution in the student sample: (1) fear of illness and death; (2) treatment experience; (3) hypochondriacal beliefs; and (4) effect of symptoms. In the patient sample, the data was best explained by a two-factor solution: (1) health related anxiety and (2) effect of symptoms and treatment experience. All scales reached good to acceptable reliability coefficients. The scales derived from the student sample and those derived from the patient sample were able to distinguish between pain patients and a matched group of normal controls. Conclusion Our data suggests that the IAS is in student samples best represented by a four factor-solution and in patient samples by a two-factor-solution. PMID:17067384

Temporal Processing of Dynamic Positron Emission Tomography via Principal Component Analysis in the Sinogram Domain

NASA Astrophysics Data System (ADS)

Chen, Zhe; Parker, B. J.; Feng, D. D.; Fulton, R.

2004-10-01

In this paper, we compare various temporal analysis schemes applied to dynamic PET for improved quantification, image quality and temporal compression purposes. We compare an optimal sampling schedule (OSS) design, principal component analysis (PCA) applied in the image domain, and principal component analysis applied in the sinogram domain; for region-of-interest quantification, sinogram-domain PCA is combined with the Huesman algorithm to quantify from the sinograms directly without requiring reconstruction of all PCA channels. Using a simulated phantom FDG brain study and three clinical studies, we evaluate the fidelity of the compressed data for estimation of local cerebral metabolic rate of glucose by a four-compartment model. Our results show that using a noise-normalized PCA in the sinogram domain gives similar compression ratio and quantitative accuracy to OSS, but with substantially better precision. These results indicate that sinogram-domain PCA for dynamic PET can be a useful preprocessing stage for PET compression and quantification applications.

Genome-wide copy number analysis reveals candidate gene loci that confer susceptibility to high-grade prostate cancer.

PubMed

Poniah, Prevathe; Mohd Zain, Shamsul; Abdul Razack, Azad Hassan; Kuppusamy, Shanggar; Karuppayah, Shankar; Sian Eng, Hooi; Mohamed, Zahurin

2017-09-01

Two key issues in prostate cancer (PCa) that demand attention currently are the need for a more precise and minimally invasive screening test owing to the inaccuracy of prostate-specific antigen and differential diagnosis to distinguish advanced vs. indolent cancers. This continues to pose a tremendous challenge in diagnosis and prognosis of PCa and could potentially lead to overdiagnosis and overtreatment complications. Copy number variations (CNVs) in the human genome have been linked to various carcinomas including PCa. Detection of these variants may improve clinical treatment as well as an understanding of the pathobiology underlying this complex disease. To this end, we undertook a pilot genome-wide CNV analysis approach in 36 subjects (18 patients with high-grade PCa and 18 controls that were matched by age and ethnicity) in search of more accurate biomarkers that could potentially explain susceptibility toward high-grade PCa. We conducted this study using the array comparative genomic hybridization technique. Array results were validated in 92 independent samples (46 high-grade PCa, 23 benign prostatic hyperplasia, and 23 healthy controls) using polymerase chain reaction-based copy number counting method. A total of 314 CNV regions were found to be unique to PCa subjects in this cohort (P<0.05). A log 2 ratio-based copy number analysis revealed 5 putative rare or novel CNV loci or both associated with susceptibility to PCa. The CNV gain regions were 1q21.3, 15q15, 7p12.1, and a novel CNV in PCa 12q23.1, harboring ARNT, THBS1, SLC5A8, and DDC genes that are crucial in the p53 and cancer pathways. A CNV loss and deletion event was observed at 8p11.21, which contains the SFRP1 gene from the Wnt signaling pathway. Cross-comparison analysis with genes associated to PCa revealed significant CNVs involved in biological processes that elicit cancer pathogenesis via cytokine production and endothelial cell proliferation. In conclusion, we postulated that the CNVs identified in this study could provide an insight into the development of advanced PCa. Copyright © 2017 Elsevier Inc. All rights reserved.

Mortality Among Men with Advanced Prostate Cancer Excluded from the ProtecT Trial.

PubMed

Johnston, Thomas J; Shaw, Greg L; Lamb, Alastair D; Parashar, Deepak; Greenberg, David; Xiong, Tengbin; Edwards, Alison L; Gnanapragasam, Vincent; Holding, Peter; Herbert, Phillipa; Davis, Michael; Mizielinsk, Elizabeth; Lane, J Athene; Oxley, Jon; Robinson, Mary; Mason, Malcolm; Staffurth, John; Bollina, Prasad; Catto, James; Doble, Andrew; Doherty, Alan; Gillatt, David; Kockelbergh, Roger; Kynaston, Howard; Prescott, Steve; Paul, Alan; Powell, Philip; Rosario, Derek; Rowe, Edward; Donovan, Jenny L; Hamdy, Freddie C; Neal, David E

2017-03-01

Early detection and treatment of asymptomatic men with advanced and high-risk prostate cancer (PCa) may improve survival rates. To determine outcomes for men diagnosed with advanced PCa following prostate-specific antigen (PSA) testing who were excluded from the ProtecT randomised trial. Mortality was compared for 492 men followed up for a median of 7.4 yr to a contemporaneous cohort of men from the UK Anglia Cancer Network (ACN) and with a matched subset from the ACN. PCa-specific and all-cause mortality were compared using Kaplan-Meier analysis and Cox's proportional hazards regression. Of the 492 men excluded from the ProtecT cohort, 37 (8%) had metastases (N1, M0=5, M1=32) and 305 had locally advanced disease (62%). The median PSA was 17μg/l. Treatments included radical prostatectomy (RP; n=54; 11%), radiotherapy (RT; n=245; 50%), androgen deprivation therapy (ADT; n=122; 25%), other treatments (n=11; 2%), and unknown (n=60; 12%). There were 49 PCa-specific deaths (10%), of whom 14 men had received radical treatment (5%); and 129 all-cause deaths (26%). In matched ProtecT and ACN cohorts, 37 (9%) and 64 (16%), respectively, died of PCa, while 89 (22%) and 103 (26%) died of all causes. ProtecT men had a 45% lower risk of death from PCa compared to matched cases (hazard ratio 0.55, 95% confidence interval 0.38-0.83; p=0.0037), but mortality was similar in those treated radically. The nonrandomised design is a limitation. Men with PSA-detected advanced PCa excluded from ProtecT and treated radically had low rates of PCa death at 7.4-yr follow-up. Among men who underwent nonradical treatment, the ProtecT group had a lower rate of PCa death. Early detection through PSA testing, leadtime bias, and group heterogeneity are possible factors in this finding. Prostate cancer that has spread outside the prostate gland without causing symptoms can be detected via prostate-specific antigen testing and treated, leading to low rates of death from this disease. Copyright © 2016 European Association of Urology. Published by Elsevier B.V. All rights reserved.

Prostate cancer risk prediction in a urology clinic in Mexico

PubMed Central

Liang, Yuanyuan; Messer, Jamie C; Louden, Christopher; Jimenez-Rios, Miguel A; Thompson, Ian M; Camarena-Reynoso, Hector R

2012-01-01

Objectives To evaluate factors affecting the risk of prostate cancer (PCa) and high-grade disease (HGPCa, Gleason score ≥7) in a Mexican referral population, with comparison to the Prostate Cancer Prevention Trial Prostate Cancer Risk Calculator (PCPTRC). Methods and Materials From a retrospective study of 826 patients who underwent prostate biopsy between January 2005 and December 2009 at the Instituto Nacional de Cancerología, Mexico, logistic regression was used to assess the effects of age, prostate-specific antigen (PSA), digital rectal exam (DRE), first-degree family history of PCa, and history of a prior prostate biopsy on PCa and HGPCa separately. Internal discrimination, goodness-of-fit and clinical utility of the resulting models were assessed with comparison to the PCPTRC. Results Rates of both PCa (73.2%) and HGPCa (33.3%) were high among referral patients in this Mexican urology clinic. The PCPTRC generally underestimated the risk of PCa but overestimated the risk of HGPCa. Four factors influencing PCa on biopsy were logPSA, DRE, family history and a prior biopsy history (all p<0.001). The internal AUC of the logistic model was 0.823 compared to 0.785 of the PCPTRC for PCa (p<0.001). The same four factors were significantly associated with HGPCa as well and the AUC was 0.779 compared to 0.766 of the PCPTRC for HGPCa (p=0.13). Conclusions Lack of screening programs or regular urological checkups in Mexico imply that men typically first reach specialized clinics with a high cancer risk. This renders diagnostic tools developed on comparatively healthy populations, such as the PCPTRC, of lesser utility. Continued efforts are needed to develop and externally validate new clinical diagnostic tools specific to high-risk referral populations incorporating new biomarkers and more clinical characteristics. PMID:22306115

Quantitative Ultrasound Using Texture Analysis of Myofascial Pain Syndrome in the Trapezius.

PubMed

Kumbhare, Dinesh A; Ahmed, Sara; Behr, Michael G; Noseworthy, Michael D

2018-01-01

Objective-The objective of this study is to assess the discriminative ability of textural analyses to assist in the differentiation of the myofascial trigger point (MTrP) region from normal regions of skeletal muscle. Also, to measure the ability to reliably differentiate between three clinically relevant groups: healthy asymptomatic, latent MTrPs, and active MTrP. Methods-18 and 19 patients were identified with having active and latent MTrPs in the trapezius muscle, respectively. We included 24 healthy volunteers. Images were obtained by research personnel, who were blinded with respect to the clinical status of the study participant. Histograms provided first-order parameters associated with image grayscale. Haralick, Galloway, and histogram-related features were used in texture analysis. Blob analysis was conducted on the regions of interest (ROIs). Principal component analysis (PCA) was performed followed by multivariate analysis of variance (MANOVA) to determine the statistical significance of the features. Results-92 texture features were analyzed for factorability using Bartlett's test of sphericity, which was significant. The Kaiser-Meyer-Olkin measure of sampling adequacy was 0.94. PCA demonstrated rotated eigenvalues of the first eight components (each comprised of multiple texture features) explained 94.92% of the cumulative variance in the ultrasound image characteristics. The 24 features identified by PCA were included in the MANOVA as dependent variables, and the presence of a latent or active MTrP or healthy muscle were independent variables. Conclusion-Texture analysis techniques can discriminate between the three clinically relevant groups.

Lack of association between NAT2 polymorphism and prostate cancer risk: a meta-analysis and trial sequential analysis

PubMed Central

Tang, Jingyuan; Xu, Lingyan; Xu, Haoxiang; Li, Ran; Han, Peng; Yang, Haiwei

2017-01-01

Previous studies have investigated the association between NAT2 polymorphism and the risk of prostate cancer (PCa). However, the findings from these studies remained inconsistent. Hence, we performed a meta-analysis to provide a more reliable conclusion about such associations. In the present meta-analysis, 13 independent case-control studies were included with a total of 14,469 PCa patients and 10,689 controls. All relevant studies published were searched in the databates PubMed, EMBASE, and Web of Science, till March 1st, 2017. We used the pooled odds ratios (ORs) with 95% confidence intervals (CIs) to evaluate the strength of the association between NAT2*4 allele and susceptibility to PCa. Subgroup analysis was carried out by ethnicity, source of controls and genotyping method. What's more, we also performed trial sequential analysis (TSA) to reduce the risk of type I error and evaluate whether the evidence of the results was firm. Firstly, our results indicated that NAT2*4 allele was not associated with PCa susceptibility (OR = 1.00, 95% CI= 0.95–1.05; P = 0.100). However, after excluding two studies for its heterogeneity and publication bias, no significant relationship was also detected between NAT2*4 allele and the increased risk of PCa, in fixed-effect model (OR = 0.99, 95% CI= 0.94–1.04; P = 0.451). Meanwhile, no significant increased risk of PCa was found in the subgroup analyses by ethnicity, source of controls and genotyping method. Moreover, TSA demonstrated that such association was confirmed in the present study. Therefore, this meta-analysis suggested that no significant association between NAT2 polymorphism and the risk of PCa was found. PMID:28915684

Clinical Significance of Retinoic Acid Receptor Beta Promoter Methylation in Prostate Cancer: A Meta-Analysis.

PubMed

Dou, MengMeng; Zhou, XueLiang; Fan, ZhiRui; Ding, XianFei; Li, LiFeng; Wang, ShuLing; Xue, Wenhua; Wang, Hui; Suo, Zhenhe; Deng, XiaoMing

2018-01-01

Retinoic acid receptor beta (RAR beta) is a retinoic acid receptor gene that has been shown to play key roles during multiple cancer processes, including cell proliferation, apoptosis, migration and invasion. Numerous studies have found that methylation of the RAR beta promoter contributed to the occurrence and development of malignant tumors. However, the connection between RAR beta promoter methylation and prostate cancer (PCa) remains unknown. This meta-analysis evaluated the clinical significance of RAR beta promoter methylation in PCa. We searched all published records relevant to RAR beta and PCa in a series of databases, including PubMed, Embase, Cochrane Library, ISI Web of Science and CNKI. The rates of RAR beta promoter methylation in the PCa and control groups (including benign prostatic hyperplasia and normal prostate tissues) were summarized. In addition, we evaluated the source region of available samples and the methods used to detect methylation. To compare the incidence and variation in RAR beta promoter methylation in PCa and non-PCa tissues, the odds ratio (OR) and 95% confidence interval (CI) were calculated accordingly. All the data were analyzed with the statistical software STATA 12.0. Based on the inclusion and exclusion criteria, 15 articles assessing 1,339 samples were further analyzed. These data showed that the RAR beta promoter methylation rates in PCa tissues were significantly higher than the rates in the non-PCa group (OR=21.65, 95% CI: 9.27-50.57). Subgroup analysis according to the source region of samples showed that heterogeneity in Asia was small (I2=0.0%, P=0.430). Additional subgroup analysis based on the method used to detect RAR beta promoter methylation showed that the heterogeneity detected by MSP (methylation-specific PCR) was relatively small (I2=11.3%, P=0.343). Although studies reported different rates for RAR beta promoter methylation in PCa tissues, the total analysis demonstrated that RAR beta promoter methylation may be correlated with PCa carcinogenesis and that the RAR beta gene is particularly susceptible. Additional studies with sufficient data are essential to further evaluate the clinical features and prognostic utility of RAR beta promoter methylation in PCa. © 2018 The Author(s). Published by S. Karger AG, Basel.

Impact of intensive horticulture practices on groundwater content of nitrates, sodium, potassium, and pesticides.

PubMed

Melo, Armindo; Pinto, Edgar; Aguiar, Ana; Mansilha, Catarina; Pinho, Olívia; Ferreira, Isabel M P L V O

2012-07-01

A monitoring program of nitrate, nitrite, potassium, sodium, and pesticides was carried out in water samples from an intensive horticulture area in a vulnerable zone from north of Portugal. Eight collecting points were selected and water-analyzed in five sampling campaigns, during 1 year. Chemometric techniques, such as cluster analysis, principal component analysis (PCA), and discriminant analysis, were used in order to understand the impact of intensive horticulture practices on dug and drilled wells groundwater and to study variations in the hydrochemistry of groundwater. PCA performed on pesticide data matrix yielded seven significant PCs explaining 77.67% of the data variance. Although PCA rendered considerable data reduction, it could not clearly group and distinguish the sample types. However, a visible differentiation between the water samples was obtained. Cluster and discriminant analysis grouped the eight collecting points into three clusters of similar characteristics pertaining to water contamination, indicating that it is necessary to improve the use of water, fertilizers, and pesticides. Inorganic fertilizers such as potassium nitrate were suspected to be the most important factors for nitrate contamination since highly significant Pearson correlation (r = 0.691, P < 0.01) was obtained between groundwater nitrate and potassium contents. Water from dug wells is especially prone to contamination from the grower and their closer neighbor's practices. Water from drilled wells is also contaminated from distant practices.

Heritable patterns of tooth decay in the permanent dentition: principal components and factor analyses.

PubMed

Shaffer, John R; Feingold, Eleanor; Wang, Xiaojing; Tcuenco, Karen T; Weeks, Daniel E; DeSensi, Rebecca S; Polk, Deborah E; Wendell, Steve; Weyant, Robert J; Crout, Richard; McNeil, Daniel W; Marazita, Mary L

2012-03-09

Dental caries is the result of a complex interplay among environmental, behavioral, and genetic factors, with distinct patterns of decay likely due to specific etiologies. Therefore, global measures of decay, such as the DMFS index, may not be optimal for identifying risk factors that manifest as specific decay patterns, especially if the risk factors such as genetic susceptibility loci have small individual effects. We used two methods to extract patterns of decay from surface-level caries data in order to generate novel phenotypes with which to explore the genetic regulation of caries. The 128 tooth surfaces of the permanent dentition were scored as carious or not by intra-oral examination for 1,068 participants aged 18 to 75 years from 664 biological families. Principal components analysis (PCA) and factor analysis (FA), two methods of identifying underlying patterns without a priori surface classifications, were applied to our data. The three strongest caries patterns identified by PCA recaptured variation represented by DMFS index (correlation, r = 0.97), pit and fissure surface caries (r = 0.95), and smooth surface caries (r = 0.89). However, together, these three patterns explained only 37% of the variability in the data, indicating that a priori caries measures are insufficient for fully quantifying caries variation. In comparison, the first pattern identified by FA was strongly correlated with pit and fissure surface caries (r = 0.81), but other identified patterns, including a second pattern representing caries of the maxillary incisors, were not representative of any previously defined caries indices. Some patterns identified by PCA and FA were heritable (h(2) = 30-65%, p = 0.043-0.006), whereas other patterns were not, indicating both genetic and non-genetic etiologies of individual decay patterns. This study demonstrates the use of decay patterns as novel phenotypes to assist in understanding the multifactorial nature of dental caries.

[Research on optimal modeling strategy for licorice extraction process based on near-infrared spectroscopy technology].

PubMed

Wang, Hai-Xia; Suo, Tong-Chuan; Yu, He-Shui; Li, Zheng

2016-10-01

The manufacture of traditional Chinese medicine (TCM) products is always accompanied by processing complex raw materials and real-time monitoring of the manufacturing process. In this study, we investigated different modeling strategies for the extraction process of licorice. Near-infrared spectra associate with the extraction time was used to detemine the states of the extraction processes. Three modeling approaches, i.e., principal component analysis (PCA), partial least squares regression (PLSR) and parallel factor analysis-PLSR (PARAFAC-PLSR), were adopted for the prediction of the real-time status of the process. The overall results indicated that PCA, PLSR and PARAFAC-PLSR can effectively detect the errors in the extraction procedure and predict the process trajectories, which has important significance for the monitoring and controlling of the extraction processes. Copyright© by the Chinese Pharmaceutical Association.

Isolation of candidate genes for apomictic development in buffelgrass (Pennisetum ciliare).

PubMed

Singh, Manjit; Burson, Byron L; Finlayson, Scott A

2007-08-01

Asexual reproduction through seeds, or apomixis, is a process that holds much promise for agricultural advances. However, the molecular mechanisms underlying apomixis are currently poorly understood. To identify genes related to female gametophyte development in apomictic ovaries of buffelgrass (Pennisetum ciliare (L.) Link), Suppression Subtractive Hybridization of ovary cDNA with leaf cDNA was performed. Through macroarray screening of subtracted cDNAs two genes were identified, Pca21 and Pca24, that showed differential expression between apomictic and sexual ovaries. Sequence analysis showed that both Pca21 and Pca24 are novel genes not previously characterized in plants. Pca21 shows homology to two wheat genes that are also expressed during reproductive development. Pca24 has similarity to coiled-coil-helix-coiled-coil-helix (CHCH) domain containing proteins from maize and sugarcane. Northern blot analysis revealed that both of these genes are expressed throughout female gametophyte development in apomictic ovaries. In situ hybridizations localized the transcript of these two genes to the developing embryo sacs in the apomictic ovaries. Based on the expression patterns it was concluded that Pca21 and Pca24 likely play a role during apomictic development in buffelgrass.

Is Emotional Congruence With Children Associated With Sexual Offending in Pedophiles and Hebephiles From the Community?

PubMed

Konrad, Anna; Kuhle, Laura F; Amelung, Till; Beier, Klaus M

2018-02-01

Although emotional congruence with children (ECWC) is a risk factor for sexual offending against children, its conceptual validity has hardly been researched. This study aims to explore the construct of ECWC by evaluating the factor structure of the Child Identification Scale (CIS-R) and its relation to facets of sexual preference and child sexual abuse behaviors. It was hypothesized that the measure comprises consistent subscales that are differently associated with aspects of sexual preference and sexual offending against children. CIS-R data of a sample of 217 adult male pedophiles from the community were used for an exploratory principal component analysis (PCA). Group comparisons and a multinomial logistic regression analysis were conducted after including a non-pedophilic control group of 22 adult men. PCA revealed a three-factor solution for the CIS-R accounting for 30% of variance. Group comparisons found differences in overall scores and the factor labeled "Attachment to Children" between subgroups of sexual age and gender preference, but not between contact, online, and non-offenders. The regression analysis showed a pedophile sexual preference and the interaction between a hebephile sexual age preference and the factor "Attachment to Children" being associated with past offending behavior. The results indicate a wish to attach to children as core feature of the CIS-R measure assessing ECWC. It is discussed whether this is an inherent feature of pedophilia or rather an independent aspect being differently distinct in pedophiles.

Transforming Graph Data for Statistical Relational Learning

DTIC Science & Technology

2012-10-01

Jordan, 2003), PLSA (Hofmann, 1999), ? Classification via RMN (Taskar et al., 2003) or SVM (Hasan, Chaoji, Salem , & Zaki, 2006) ? Hierarchical...dimensionality reduction methods such as Principal 407 Rossi, McDowell, Aha, & Neville Component Analysis (PCA), Principal Factor Analysis ( PFA ), and...clustering algorithm. Journal of the Royal Statistical Society. Series C, Applied statistics, 28, 100–108. Hasan, M. A., Chaoji, V., Salem , S., & Zaki, M

Prostate-Specific Antigen (PSA) Screening and New Biomarkers for Prostate Cancer (PCa)

PubMed Central

Rittenhouse, Harry; Hu, Xinhai; Cammann, Henning; Jung, Klaus

2014-01-01

Abstract PSA screening reduces PCa-mortality but the disadvantages overdiagnosis and overtreatment require multivariable risk-prediction tools to select appropriate treatment or active surveillance. This review explains the differences between the two largest screening trials and discusses the drawbacks of screening and its meta-analysisxs. The current American and European screening strategies are described. Nonetheless, PSA is one of the most widely used tumor markers and strongly correlates with the risk of harboring PCa. However, while PSA has limitations for PCa detection with its low specificity there are several potential biomarkers presented in this review with utility for PCa currently being studied. There is an urgent need for new biomarkers especially to detect clinically significant and aggressive PCa. From all PSA-based markers, the FDA-approved prostate health index (phi) shows improved specificity over percent free and total PSA. Another kallikrein panel, 4K, which includes KLK2 has recently shown promise in clinical research studies but has not yet undergone formal validation studies. In urine, prostate cancer gene 3 (PCA3) has also been validated and approved by the FDA for its utility to detect PCa. The potential correlation of PCA3 with cancer aggressiveness requires more clinical studies. The detection of the fusion of androgen-regulated genes with genes of the regulatory transcription factors in tissue of ~50% of all PCa-patients is a milestone in PCa research. A combination of the urinary assays for TMPRSS2:ERG gene fusion and PCA3 shows an improved accuracy for PCa detection. Overall, the field of PCa biomarker discovery is very exciting and prospective. PMID:27683457

Exploring the Factor Structure of Neurocognitive Measures in Older Individuals

PubMed Central

Santos, Nadine Correia; Costa, Patrício Soares; Amorim, Liliana; Moreira, Pedro Silva; Cunha, Pedro; Cotter, Jorge; Sousa, Nuno

2015-01-01

Here we focus on factor analysis from a best practices point of view, by investigating the factor structure of neuropsychological tests and using the results obtained to illustrate on choosing a reasonable solution. The sample (n=1051 individuals) was randomly divided into two groups: one for exploratory factor analysis (EFA) and principal component analysis (PCA), to investigate the number of factors underlying the neurocognitive variables; the second to test the “best fit” model via confirmatory factor analysis (CFA). For the exploratory step, three extraction (maximum likelihood, principal axis factoring and principal components) and two rotation (orthogonal and oblique) methods were used. The analysis methodology allowed exploring how different cognitive/psychological tests correlated/discriminated between dimensions, indicating that to capture latent structures in similar sample sizes and measures, with approximately normal data distribution, reflective models with oblimin rotation might prove the most adequate. PMID:25880732

Meta-analysis of CDKN2A methylation to find its role in prostate cancer development and progression, and also to find the effect of CDKN2A expression on disease-free survival (PRISMA).

PubMed

Cao, Zipei; Wei, Lijuan; Zhu, Weizhi; Yao, Xuping

2018-03-01

Reduction of cyclin-dependent kinase inhibitor 2A (CDKN2A) (p16 and p14) expression through DNA methylation has been reported in prostate cancer (PCa). This meta-analysis was conducted to assess the difference of p16 and p14 methylation between PCa and different histological types of nonmalignant controls and the correlation of p16 or p14 methylation with clinicopathological features of PCa. According to the preferred reporting items for systematic reviews and meta-analyses (PRISMA) statement criteria, articles were searched in PubMed, Embase, EBSCO, Wanfang, and CNKI databases. The strength of correlation was calculated by the pooled odds ratios (ORs) and their corresponding 95% confidence intervals (95% CIs). Trial sequential analysis (TSA) was used to estimate the required population information for significant results. A total of 20 studies published from 1997 to 2017 were identified in this meta-analysis, including 1140 PCa patients and 530 cases without cancer. Only p16 methylation in PCa was significantly higher than in benign prostatic lesions (OR = 4.72, P = .011), but had a similar level in PCa and adjacent tissues or high-grade prostatic intraepithelial neoplasias (HGPIN). TSA revealed that this analysis on p16 methylation is a false positive result in cancer versus benign prostatic lesions (the estimated required information size of 5116 participants). p16 methylation was not correlated with PCa in the urine and blood. Besides, p16 methylation was not linked to clinical stage, prostate-specific antigen (PSA) level, and Gleason score (GS) of patients with PCa. p14 methylation was not correlated with PCa in tissue and urine samples. No correlation was observed between p14 methylation and clinical stage or GS. CDKN2A mutation and copy number alteration were not associated with prognosis of PCa in overall survival and disease-free survival. CDKN2A expression was not correlated with the prognosis of PCa in overall survival (492 cases) (P > .1), while CDKN2A expression was significantly associated with a poor disease-free survival (P < .01). CDKN2A methylation may not be significantly associated with the development, progression of PCa. Although CDKN2A expression had an unfavorable prognosis in disease-free survival. More studies are needed to confirm our results.

Fluorescence Intrinsic Characterization of Excitation-Emission Matrix Using Multi-Dimensional Ensemble Empirical Mode Decomposition

PubMed Central

Chang, Chi-Ying; Chang, Chia-Chi; Hsiao, Tzu-Chien

2013-01-01

Excitation-emission matrix (EEM) fluorescence spectroscopy is a noninvasive method for tissue diagnosis and has become important in clinical use. However, the intrinsic characterization of EEM fluorescence remains unclear. Photobleaching and the complexity of the chemical compounds make it difficult to distinguish individual compounds due to overlapping features. Conventional studies use principal component analysis (PCA) for EEM fluorescence analysis, and the relationship between the EEM features extracted by PCA and diseases has been examined. The spectral features of different tissue constituents are not fully separable or clearly defined. Recently, a non-stationary method called multi-dimensional ensemble empirical mode decomposition (MEEMD) was introduced; this method can extract the intrinsic oscillations on multiple spatial scales without loss of information. The aim of this study was to propose a fluorescence spectroscopy system for EEM measurements and to describe a method for extracting the intrinsic characteristics of EEM by MEEMD. The results indicate that, although PCA provides the principal factor for the spectral features associated with chemical compounds, MEEMD can provide additional intrinsic features with more reliable mapping of the chemical compounds. MEEMD has the potential to extract intrinsic fluorescence features and improve the detection of biochemical changes. PMID:24240806

Epigenetics-related genes in prostate cancer: expression profile in prostate cancer tissues, androgen-sensitive and -insensitive cell lines.

PubMed

Shaikhibrahim, Zaki; Lindstrot, Andreas; Ochsenfahrt, Jacqueline; Fuchs, Kerstin; Wernert, Nicolas

2013-01-01

Epigenetic changes have been suggested to drive prostate cancer (PCa) development and progression. Therefore, in this study, we aimed to identify novel epigenetics-related genes in PCa tissues, and to examine their expression in metastatic PCa cell lines. We analyzed the expression of epigenetics-related genes via a clustering analysis based on gene function in moderately and poorly differentiated PCa glands compared to normal glands of the peripheral zone (prostate proper) from PCa patients using Whole Human Genome Oligo Microarrays. Our analysis identified 12 epigenetics-related genes with a more than 2-fold increase or decrease in expression and a p-value <0.01. In modera-tely differentiated tumors compared to normal glands of the peripheral zone, we found the genes, TDRD1, IGF2, DICER1, ADARB1, HILS1, GLMN and TRIM27, to be upregulated, whereas TNRC6A and DGCR8 were found to be downregulated. In poorly differentiated tumors, we found TDRD1, ADARB and RBM3 to be upregulated, whereas DGCR8, PIWIL2 and BC069781 were downregulated. Our analysis of the expression level for each gene in the metastatic androgen-sensitive VCaP and LNCaP, and -insensitive PC3 and DU-145 PCa cell lines revealed differences in expression among the cell lines which may reflect the different biological properties of each cell line, and the potential role of each gene at different metastatic sites. The novel epigenetics-related genes that we identified in primary PCa tissues may provide further insight into the role that epigenetic changes play in PCa. Moreover, some of the genes that we identified may play important roles in primary PCa and metastasis, in primary PCa only, or in metastasis only. Follow-up studies are required to investigate the functional role and the role that the expression of these genes play in the outcome and progression of PCa using tissue microarrays.

Two worlds collide: Image analysis methods for quantifying structural variation in cluster molecular dynamics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Steenbergen, K. G., E-mail: kgsteen@gmail.com; Gaston, N.

2014-02-14

Inspired by methods of remote sensing image analysis, we analyze structural variation in cluster molecular dynamics (MD) simulations through a unique application of the principal component analysis (PCA) and Pearson Correlation Coefficient (PCC). The PCA analysis characterizes the geometric shape of the cluster structure at each time step, yielding a detailed and quantitative measure of structural stability and variation at finite temperature. Our PCC analysis captures bond structure variation in MD, which can be used to both supplement the PCA analysis as well as compare bond patterns between different cluster sizes. Relying only on atomic position data, without requirement formore » a priori structural input, PCA and PCC can be used to analyze both classical and ab initio MD simulations for any cluster composition or electronic configuration. Taken together, these statistical tools represent powerful new techniques for quantitative structural characterization and isomer identification in cluster MD.« less

Two worlds collide: image analysis methods for quantifying structural variation in cluster molecular dynamics.

PubMed

Steenbergen, K G; Gaston, N

2014-02-14

Inspired by methods of remote sensing image analysis, we analyze structural variation in cluster molecular dynamics (MD) simulations through a unique application of the principal component analysis (PCA) and Pearson Correlation Coefficient (PCC). The PCA analysis characterizes the geometric shape of the cluster structure at each time step, yielding a detailed and quantitative measure of structural stability and variation at finite temperature. Our PCC analysis captures bond structure variation in MD, which can be used to both supplement the PCA analysis as well as compare bond patterns between different cluster sizes. Relying only on atomic position data, without requirement for a priori structural input, PCA and PCC can be used to analyze both classical and ab initio MD simulations for any cluster composition or electronic configuration. Taken together, these statistical tools represent powerful new techniques for quantitative structural characterization and isomer identification in cluster MD.

Percentage of positive prostate biopsies independently predicts biochemical outcome following radiation therapy for prostate cancer.

PubMed

Gabriele, Domenico; Garibaldi, Monica; Girelli, Giuseppe; Taraglio, Stefano; Duregon, Eleonora; Gabriele, Pietro; Guiot, Caterina; Bollito, Enrico

2016-06-01

This work aims to definitely show the ability of percentage of positive biopsy cores (%PC) to independently predict biochemical outcome beyond traditional pretreatment risk-factors in prostate cancer (PCa) patients treated with radiotherapy. A cohort of 2493 men belonging to the EUREKA-2 retrospective multicentric database on (PCa) and treated with external-beam radiation therapy (EBRT) as primary treatment comprised the study population (median follow-up 50 months). A Cox regression time to prostate-specific antigen (PSA) failure analysis was performed to evaluate the predictive power of %PC, both in univariate and multivariate settings, with age, pretreatment PSA, clinical-radiological staging, bioptic Gleason Score (bGS), RT dose and RT +/- ADT as covariates. P statistics for %PC is lower than 0.001 both in univariate and multivariate models. %PC as a continuous variable yields an AUC of 69% in ROC curve analysis for biochemical relapse. Four classes of %PC (1-20%, 21-50%, 51-80% and 81-100%) distinctly split patients for risk of biochemical relapse (overall log-rank test P<0.0001), with biochemical progression free survival (bPFS) at 5-years ranging from 88% to 58% and 10-years bPFS ranging from 80% to 38%. We strongly affirm the usefulness of %PC information beyond main risk factors (PSA, staging and bGS) in predicting biochemical recurrence after EBRT for PCa. The stratification of patients according to %PC may be valuable to further discriminate cases with favourable or adverse prognosis.

Different approaches in Partial Least Squares and Artificial Neural Network models applied for the analysis of a ternary mixture of Amlodipine, Valsartan and Hydrochlorothiazide

NASA Astrophysics Data System (ADS)

Darwish, Hany W.; Hassan, Said A.; Salem, Maissa Y.; El-Zeany, Badr A.

2014-03-01

Different chemometric models were applied for the quantitative analysis of Amlodipine (AML), Valsartan (VAL) and Hydrochlorothiazide (HCT) in ternary mixture, namely, Partial Least Squares (PLS) as traditional chemometric model and Artificial Neural Networks (ANN) as advanced model. PLS and ANN were applied with and without variable selection procedure (Genetic Algorithm GA) and data compression procedure (Principal Component Analysis PCA). The chemometric methods applied are PLS-1, GA-PLS, ANN, GA-ANN and PCA-ANN. The methods were used for the quantitative analysis of the drugs in raw materials and pharmaceutical dosage form via handling the UV spectral data. A 3-factor 5-level experimental design was established resulting in 25 mixtures containing different ratios of the drugs. Fifteen mixtures were used as a calibration set and the other ten mixtures were used as validation set to validate the prediction ability of the suggested methods. The validity of the proposed methods was assessed using the standard addition technique.

Wisteria floribunda Agglutinin and Its Reactive-Glycan-Carrying Prostate-Specific Antigen as a Novel Diagnostic and Prognostic Marker of Prostate Cancer

PubMed Central

Hagiwara, Kazuhisa; Tobisawa, Yuki; Kaya, Takatoshi; Kaneko, Tomonori; Hatakeyama, Shingo; Mori, Kazuyuki; Hashimoto, Yasuhiro; Koie, Takuya; Suda, Yoshihiko; Ohyama, Chikara; Yoneyama, Tohru

2017-01-01

Wisteria floribunda agglutinin (WFA) preferably binds to LacdiNAc glycans, and its reactivity is associated with tumor progression. The aim of this study to examine whether the serum LacdiNAc carrying prostate-specific antigen–glycosylation isomer (PSA-Gi) and WFA-reactivity of tumor tissue can be applied as a diagnostic and prognostic marker of prostate cancer (PCa). Between 2007 and 2016, serum PSA-Gi levels before prostate biopsy (Pbx) were measured in 184 biopsy-proven benign prostatic hyperplasia patients and 244 PCa patients using an automated lectin-antibody immunoassay. WFA-reactivity on tumor was analyzed in 260 radical prostatectomy (RP) patients. Diagnostic and prognostic performance of serum PSA-Gi was evaluated using area under the receiver-operator characteristic curve (AUC). Prognostic performance of WFA-reactivity on tumor was evaluated via Cox proportional hazards regression analysis and nomogram. The AUC of serum PSA-Gi detecting PCa and predicting Pbx Grade Group (GG) 3 and GG ≥ 3 after RP was much higher than those of conventional PSA. Multivariate analysis showed that WFA-reactivity on prostate tumor was an independent risk factor of PSA recurrence. The nomogram was a strong model for predicting PSA-free survival provability with a c-index ≥0.7. Serum PSA-Gi levels and WFA-reactivity on prostate tumor may be a novel diagnostic and pre- and post-operative prognostic biomarkers of PCa, respectively. PMID:28134773

Wisteria floribunda Agglutinin and Its Reactive-Glycan-Carrying Prostate-Specific Antigen as a Novel Diagnostic and Prognostic Marker of Prostate Cancer.

PubMed

Hagiwara, Kazuhisa; Tobisawa, Yuki; Kaya, Takatoshi; Kaneko, Tomonori; Hatakeyama, Shingo; Mori, Kazuyuki; Hashimoto, Yasuhiro; Koie, Takuya; Suda, Yoshihiko; Ohyama, Chikara; Yoneyama, Tohru

2017-01-26

Wisteria floribunda agglutinin (WFA) preferably binds to LacdiNAc glycans, and its reactivity is associated with tumor progression. The aim of this study to examine whether the serum LacdiNAc carrying prostate-specific antigen-glycosylation isomer (PSA-Gi) and WFA-reactivity of tumor tissue can be applied as a diagnostic and prognostic marker of prostate cancer (PCa). Between 2007 and 2016, serum PSA-Gi levels before prostate biopsy (Pbx) were measured in 184 biopsy-proven benign prostatic hyperplasia patients and 244 PCa patients using an automated lectin-antibody immunoassay. WFA-reactivity on tumor was analyzed in 260 radical prostatectomy (RP) patients. Diagnostic and prognostic performance of serum PSA-Gi was evaluated using area under the receiver-operator characteristic curve (AUC). Prognostic performance of WFA-reactivity on tumor was evaluated via Cox proportional hazards regression analysis and nomogram. The AUC of serum PSA-Gi detecting PCa and predicting Pbx Grade Group (GG) 3 and GG ≥ 3 after RP was much higher than those of conventional PSA. Multivariate analysis showed that WFA-reactivity on prostate tumor was an independent risk factor of PSA recurrence. The nomogram was a strong model for predicting PSA-free survival provability with a c -index ≥0.7. Serum PSA-Gi levels and WFA-reactivity on prostate tumor may be a novel diagnostic and pre- and post-operative prognostic biomarkers of PCa, respectively.

Differential research of inflammatory and related mediators in BPH, histological prostatitis and PCa.

PubMed

Huang, T R; Wang, G C; Zhang, H M; Peng, B

2018-02-14

Prostate cancer (PCa) is one of the most common male malignancies in the world. It was aimed to investigate differential expression of inflammatory and related factors in benign prostatic hyperplasia (BPH), prostate cancer (PCa), histological prostatitis (HP) and explore the role of Inducible nitric oxide synthase (iNOS), (VEGF) Vascular endothelial growth factor, androgen receptor (AR) and IL-2, IL-8 and TNF-α in the occurrence and development of prostate cancer. RT-PCR was used to detect the mRNA expression level of iNOS, VEGF, AR and IL-2, IL-8 and TNF-α in BPH, PCa and BPH+HP. Western blotting and immunohistochemical staining were used to detect the protein levels of various proteins in three diseases. The results showed the mRNA and protein levels of iNOS, VEGF and IL-2, IL-8 and TNF-α were significantly increased in PCa and BPH+HP groups compared with BPH group (p < .05), while the AR was significantly lower than those in PCa and BPH+HP groups (p < .05). There was no significant difference in the mRNA and protein levels of iNOS, VEGF, AR and IL-2, IL-8 and TNF-α between PCa and BPH+HP groups (p > .05). iNOS, VEGF, AR and IL-2, IL-8 and TNF-α are involved in the malignant transformation of prostate tissue and play an important role in the development and progression of Prostate cancer (PCa). © 2018 Blackwell Verlag GmbH.

Evaluation of Soil Contamination Indices in a Mining Area of Jiangxi, China

PubMed Central

Wu, Jin; Teng, Yanguo; Lu, Sijin; Wang, Yeyao; Jiao, Xudong

2014-01-01

There is currently a wide variety of methods used to evaluate soil contamination. We present a discussion of the advantages and limitations of different soil contamination assessment methods. In this study, we analyzed seven trace elements (As, Cd, Cr, Cu, Hg, Pb, and Zn) that are indicators of soil contamination in Dexing, a city in China that is famous for its vast nonferrous mineral resources in China, using enrichment factor (EF), geoaccumulation index (Igeo), pollution index (PI), and principal component analysis (PCA). The three contamination indices and PCA were then mapped to understand the status and trends of soil contamination in this region. The entire study area is strongly enriched in Cd, Cu, Pb, and Zn, especially in areas near mine sites. As and Hg were also present in high concentrations in urban areas. Results indicated that Cr in this area originated from both anthropogenic and natural sources. PCA combined with Geographic Information System (GIS) was successfully used to discriminate between natural and anthropogenic trace metals. PMID:25397401

Identification of an IL-1-induced gene expression pattern in AR+ PCa cells that mimics the molecular phenotype of AR- PCa cells.

PubMed

Thomas-Jardin, Shayna E; Kanchwala, Mohammed S; Jacob, Joan; Merchant, Sana; Meade, Rachel K; Gahnim, Nagham M; Nawas, Afshan F; Xing, Chao; Delk, Nikki A

2018-06-01

In immunosurveillance, bone-derived immune cells infiltrate the tumor and secrete inflammatory cytokines to destroy cancer cells. However, cancer cells have evolved mechanisms to usurp inflammatory cytokines to promote tumor progression. In particular, the inflammatory cytokine, interleukin-1 (IL-1), is elevated in prostate cancer (PCa) patient tissue and serum, and promotes PCa bone metastasis. IL-1 also represses androgen receptor (AR) accumulation and activity in PCa cells, yet the cells remain viable and tumorigenic; suggesting that IL-1 may also contribute to AR-targeted therapy resistance. Furthermore, IL-1 and AR protein levels negatively correlate in PCa tumor cells. Taken together, we hypothesize that IL-1 reprograms AR positive (AR + ) PCa cells into AR negative (AR - ) PCa cells that co-opt IL-1 signaling to ensure AR-independent survival and tumor progression in the inflammatory tumor microenvironment. LNCaP and PC3 PCa cells were treated with IL-1β or HS-5 bone marrow stromal cell (BMSC) conditioned medium and analyzed by RNA sequencing and RT-QPCR. To verify genes identified by RNA sequencing, LNCaP, MDA-PCa-2b, PC3, and DU145 PCa cell lines were treated with the IL-1 family members, IL-1α or IL-1β, or exposed to HS-5 BMSC in the presence or absence of Interleukin-1 Receptor Antagonist (IL-1RA). Treated cells were analyzed by western blot and/or RT-QPCR. Comparative analysis of sequencing data from the AR + LNCaP PCa cell line versus the AR - PC3 PCa cell line reveals an IL-1-conferred gene suite in LNCaP cells that is constitutive in PC3 cells. Bioinformatics analysis of the IL-1 regulated gene suite revealed that inflammatory and immune response pathways are primarily elicited; likely facilitating PCa cell survival and tumorigenicity in an inflammatory tumor microenvironment. Our data supports that IL-1 reprograms AR + PCa cells to mimic AR - PCa gene expression patterns that favor AR-targeted treatment resistance and cell survival. © 2018 Wiley Periodicals, Inc.

PCA-LBG-based algorithms for VQ codebook generation

NASA Astrophysics Data System (ADS)

Tsai, Jinn-Tsong; Yang, Po-Yuan

2015-04-01

Vector quantisation (VQ) codebooks are generated by combining principal component analysis (PCA) algorithms with Linde-Buzo-Gray (LBG) algorithms. All training vectors are grouped according to the projected values of the principal components. The PCA-LBG-based algorithms include (1) PCA-LBG-Median, which selects the median vector of each group, (2) PCA-LBG-Centroid, which adopts the centroid vector of each group, and (3) PCA-LBG-Random, which randomly selects a vector of each group. The LBG algorithm finds a codebook based on the better vectors sent to an initial codebook by the PCA. The PCA performs an orthogonal transformation to convert a set of potentially correlated variables into a set of variables that are not linearly correlated. Because the orthogonal transformation efficiently distinguishes test image vectors, the proposed PCA-LBG-based algorithm is expected to outperform conventional algorithms in designing VQ codebooks. The experimental results confirm that the proposed PCA-LBG-based algorithms indeed obtain better results compared to existing methods reported in the literature.

E-selectin ligand-1 controls circulating prostate cancer cell rolling/adhesion and metastasis

PubMed Central

Yasmin-Karim, Sayeda; King, Michael R.; Messing, Edward M.; Lee, Yi-Fen

2014-01-01

Circulating prostate cancer (PCa) cells preferentially roll and adhere on bone marrow vascular endothelial cells, where abundant E-selectin and stromal cell-derived factor 1 (SDF-1) are expressed, subsequently initiating a cascade of activation events that eventually lead to the development of metastases. To elucidate the roles of circulating PCa cells' rolling and adhesion behaviors in cancer metastases, we applied a dynamic cylindrical flow-based microchannel device that is coated with E-selectin and SDF-1, mimicking capillary endothelium. Using this device we captured a small fraction of rolling PCa cells. These rolling cells display higher static adhesion ability, more aggressive cancer phenotypes and stem-like properties. Importantly, mice received rolling PCa cells, but not floating PCa cells, developed cancer metastases. Genes coding for E-selectin ligands and genes associated with cancer stem cells and metastasis were elevated in rolling PCa cells. Knock down of E-selectin ligand 1(ESL-1), significantly impaired PCa cells' rolling capacity and reduced cancer aggressiveness. Moreover, ESL-1 activates RAS and MAP kinase signal cascade, consequently inducing the downstream targets. In summary, circulating PCa cells' rolling capacity contributes to PCa metastasis, and that is in part controlled by ESL-1. PMID:25301730

Novel targets for prostate cancer chemoprevention

PubMed Central

Sarkar, Fazlul H; Li, Yiwei; Wang, Zhiwei; Kong, Dejuan

2010-01-01

Among many endocrine-related cancers, prostate cancer (PCa) is the most frequent male malignancy, and it is the second most common cause of cancer-related death in men in the United States. Therefore, this review focuses on summarizing the knowledge of molecular signaling pathways in PCa because, in order to better design new preventive strategies for the fight against PCa, documentation of the knowledge on the pathogenesis of PCa at the molecular level is very important. Cancer cells are known to have alterations in multiple cellular signaling pathways; indeed, the development and the progression of PCa are known to be caused by the deregulation of several selective signaling pathways such as the androgen receptor, Akt, nuclear factor-κB, Wnt, Hedgehog, and Notch. Therefore, strategies targeting these important pathways and their upstream and downstream signaling could be promising for the prevention of PCa progression. In this review, we summarize the current knowledge regarding the alterations in cell signaling pathways during the development and progression of PCa, and document compelling evidence showing that these are the targets of several natural agents against PCa progression and its metastases. PMID:20576802

Public knowledge and beliefs about depression among urban and rural Malays in Malaysia.

PubMed

Swami, Viren; Loo, Phik-Wern; Furnham, Adrian

2010-09-01

This study examined knowledge and beliefs about depression among Malaysian Malays varying in socioeconomic status. A total of 153 urban and 189 rural participants completed a questionnaire in which they had to identify two cases of depression and rate a series of items about the causes and best treatments for depression. Results showed that urban participants were more likely to use psychiatric labels ('depression') for the two vignettes, whereas rural participants tended to use more generic terms ('emotional stress'). Principal components analysis (PCA) showed that beliefs about the causes of depression factored into five components, of which stressful life events was most strongly endorsed by both groups. PCA of treatment items revealed four stable components, of which religious factors were most strongly endorsed. There were also a number of significant between-group differences in the endorsement of these factors (eta(p) (2) = .03-.11), with rural participants generally rating supernatural and religious factors more strongly than urban Malays. These results are discussed in relation to mental health literacy programmes in Malaysia.

Discrimination of Geographical Origin of Asian Garlic Using Isotopic and Chemical Datasets under Stepwise Principal Component Analysis.

PubMed

Liu, Tsang-Sen; Lin, Jhen-Nan; Peng, Tsung-Ren

2018-01-16

Isotopic compositions of δ 2 H, δ 18 O, δ 13 C, and δ 15 N and concentrations of 22 trace elements from garlic samples were analyzed and processed with stepwise principal component analysis (PCA) to discriminate garlic's country of origin among Asian regions including South Korea, Vietnam, Taiwan, and China. Results indicate that there is no single trace-element concentration or isotopic composition that can accomplish the study's purpose and the stepwise PCA approach proposed does allow for discrimination between countries on a regional basis. Sequentially, Step-1 PCA distinguishes garlic's country of origin among Taiwanese, South Korean, and Vietnamese samples; Step-2 PCA discriminates Chinese garlic from South Korean garlic; and Step-3 and Step-4 PCA, Chinese garlic from Vietnamese garlic. In model tests, countries of origin of all audit samples were correctly discriminated by stepwise PCA. Consequently, this study demonstrates that stepwise PCA as applied is a simple and effective approach to discriminating country of origin among Asian garlics. © 2018 American Academy of Forensic Sciences.

Inter-comparison of receptor models for PM source apportionment: Case study in an industrial area

NASA Astrophysics Data System (ADS)

Viana, M.; Pandolfi, M.; Minguillón, M. C.; Querol, X.; Alastuey, A.; Monfort, E.; Celades, I.

2008-05-01

Receptor modelling techniques are used to identify and quantify the contributions from emission sources to the levels and major and trace components of ambient particulate matter (PM). A wide variety of receptor models are currently available, and consequently the comparability between models should be evaluated if source apportionment data are to be used as input in health effects studies or mitigation plans. Three of the most widespread receptor models (principal component analysis, PCA; positive matrix factorization, PMF; chemical mass balance, CMB) were applied to a single PM10 data set (n=328 samples, 2002-2005) obtained from an industrial area in NE Spain, dedicated to ceramic production. Sensitivity and temporal trend analyses (using the Mann-Kendall test) were applied. Results evidenced the good overall performance of the three models (r2>0.83 and α>0.91×between modelled and measured PM10 mass), with a good agreement regarding source identification and high correlations between input (CMB) and output (PCA, PMF) source profiles. Larger differences were obtained regarding the quantification of source contributions (up to a factor of 4 in some cases). The combined application of different types of receptor models would solve the limitations of each of the models, by constructing a more robust solution based on their strengths. The authors suggest the combined use of factor analysis techniques (PCA, PMF) to identify and interpret emission sources, and to obtain a first quantification of their contributions to the PM mass, and the subsequent application of CMB. Further research is needed to ensure that source apportionment methods are robust enough for application to PM health effects assessments.

Revealing Sources and Distribution Changes of Dissolved Organic Matter (DOM) in Pore Water of Sediment from the Yangtze Estuary

PubMed Central

Wang, Ying; Zhang, Di; Shen, Zhenyao; Feng, Chenghong; Chen, Jing

2013-01-01

Dissolved organic matter (DOM) in sediment pore waters from Yangtze estuary of China based on abundance, UV absorbance, molecular weight distribution and fluorescence were investigated using a combination of various parameters of DOM as well as 3D fluorescence excitation emission matrix spectra (F-EEMS) with the parallel factor and principal component analysis (PARAFAC-PCA). The results indicated that DOM in pore water of Yangtze estuary was very variable which mainly composed of low aromaticity and molecular weight materials. Three humic-like substances (C1, C2, C4) and one protein-like substance (C3) were identified by PARAFAC model. C1, C2 and C4 exhibited same trends and were very similar. The separation of samples on both axes of the PCA showed the difference in DOM properties. C1, C2 and C4 concurrently showed higher positive factor 1 loadings, while C3 showed highly positive factor 2 loadings. The PCA analysis showed a combination contribution of microbial DOM signal and terrestrial DOM signal in the Yangtze estuary. Higher and more variable DOM abundance, aromaticity and molecular weight of surface sediment pore water DOM can be found in the southern nearshore than the other regions primarily due to the influence of frequent and intensive human activities and tributaries inflow in this area. The DOM abundance, aromaticity, molecular weight and fluorescence intensity in core of different depth were relative constant and increased gradually with depth. DOM in core was mainly composed of humic-like material, which was due to higher release of the sedimentary organic material into the porewater during early diagenesis. PMID:24155904

Plaque echodensity and textural features are associated with histologic carotid plaque instability.

PubMed

Doonan, Robert J; Gorgui, Jessica; Veinot, Jean P; Lai, Chi; Kyriacou, Efthyvoulos; Corriveau, Marc M; Steinmetz, Oren K; Daskalopoulou, Stella S

2016-09-01

Carotid plaque echodensity and texture features predict cerebrovascular symptomatology. Our purpose was to determine the association of echodensity and textural features obtained from a digital image analysis (DIA) program with histologic features of plaque instability as well as to identify the specific morphologic characteristics of unstable plaques. Patients scheduled to undergo carotid endarterectomy were recruited and underwent carotid ultrasound imaging. DIA was performed to extract echodensity and textural features using Plaque Texture Analysis software (LifeQ Medical Ltd, Nicosia, Cyprus). Carotid plaque surgical specimens were obtained and analyzed histologically. Principal component analysis (PCA) was performed to reduce imaging variables. Logistic regression models were used to determine if PCA variables and individual imaging variables predicted histologic features of plaque instability. Image analysis data from 160 patients were analyzed. Individual imaging features of plaque echolucency and homogeneity were associated with a more unstable plaque phenotype on histology. These results were independent of age, sex, and degree of carotid stenosis. PCA reduced 39 individual imaging variables to five PCA variables. PCA1 and PCA2 were significantly associated with overall plaque instability on histology (both P = .02), whereas PCA3 did not achieve statistical significance (P = .07). DIA features of carotid plaques are associated with histologic plaque instability as assessed by multiple histologic features. Importantly, unstable plaques on histology appear more echolucent and homogeneous on ultrasound imaging. These results are independent of stenosis, suggesting that image analysis may have a role in refining the selection of patients who undergo carotid endarterectomy. Copyright © 2016 Society for Vascular Surgery. Published by Elsevier Inc. All rights reserved.

Testing the Technology Acceptance Model: HIV case managers' intention to use a continuity of care record with context-specific links.

PubMed

Schnall, Rebecca; Bakken, Suzanne

2011-09-01

To assess the applicability of the Technology Acceptance Model (TAM) constructs in explaining HIV case managers' behavioural intention to use a continuity of care record (CCR) with context-specific links designed to meet their information needs. Data were collected from 94 case managers who provide care to persons living with HIV (PLWH) using an online survey comprising three components: (1) demographic information: age, gender, ethnicity, race, Internet usage and computer experience; (2) mock-up of CCR with context-specific links; and items related to TAM constructs. Data analysis included: principal components factor analysis (PCA), assessment of internal consistency reliability and univariate and multivariate analysis. PCA extracted three factors (Perceived Ease of Use, Perceived Usefulness and Perceived Barriers to Use), explained variance = 84.9%, Cronbach's ά = 0.69-0.91. In a linear regression model, Perceived Ease of Use, Perceived Usefulness and Perceived Barriers to Use explained 43.6% (p < 0.001) of the variance in Behavioural Intention to use a CCR with context-specific links. Our study contributes to the evidence base regarding TAM in health care through expanding the type of professional surveyed, study setting and Health Information Technology assessed.

Bayesian inference of the number of factors in gene-expression analysis: application to human virus challenge studies

PubMed Central

2010-01-01

Background Nonparametric Bayesian techniques have been developed recently to extend the sophistication of factor models, allowing one to infer the number of appropriate factors from the observed data. We consider such techniques for sparse factor analysis, with application to gene-expression data from three virus challenge studies. Particular attention is placed on employing the Beta Process (BP), the Indian Buffet Process (IBP), and related sparseness-promoting techniques to infer a proper number of factors. The posterior density function on the model parameters is computed using Gibbs sampling and variational Bayesian (VB) analysis. Results Time-evolving gene-expression data are considered for respiratory syncytial virus (RSV), Rhino virus, and influenza, using blood samples from healthy human subjects. These data were acquired in three challenge studies, each executed after receiving institutional review board (IRB) approval from Duke University. Comparisons are made between several alternative means of per-forming nonparametric factor analysis on these data, with comparisons as well to sparse-PCA and Penalized Matrix Decomposition (PMD), closely related non-Bayesian approaches. Conclusions Applying the Beta Process to the factor scores, or to the singular values of a pseudo-SVD construction, the proposed algorithms infer the number of factors in gene-expression data. For real data the "true" number of factors is unknown; in our simulations we consider a range of noise variances, and the proposed Bayesian models inferred the number of factors accurately relative to other methods in the literature, such as sparse-PCA and PMD. We have also identified a "pan-viral" factor of importance for each of the three viruses considered in this study. We have identified a set of genes associated with this pan-viral factor, of interest for early detection of such viruses based upon the host response, as quantified via gene-expression data. PMID:21062443

Validation of the Marijuana Effect Expectancy Questionnaire-Brief

ERIC Educational Resources Information Center

Torrealday, O.; Stein, L. A. R.; Barnett, N.; Golembeske, C.; Lebeau, R.; Colby, S. M.; Monti, P. M.

2008-01-01

The purpose of this study was to evaluate a brief version of the Marijuana Effect Expectancy Questionnaire (MEEQ; Schafer & Brown, 1991). The original MEEQ was reduced to 6 items (MEEQ-B). Principal component analysis (PCA) was performed and two factors were identified (positive effects and negative effects) accounting for 52.3% of the variance.…

Ethnobotanical knowledge in rural communities of Cordoba (Argentina): the importance of cultural and biogeographical factors

PubMed Central

2009-01-01

Background The possibility to better understand the relationships within the men, the nature and their culture has extreme importance because allows the characterisation of social systems through their particular environmental perception, and provides useful tools for the development of conservation policies. Methods The present study was planned to disentangle environmental and cultural factors that are influencing the perception, knowledge and uses of edible and medicinal plants in rural communities of Cordoba (Argentina). Interviews an participant observation were conducted in nine rural communities located in three different biogeographical areas. Data about knowledge of medicinal and edible plants and sociocultural variables were obtained. Data were analysed by Principal Components Analysis (PCA). Results The analysis of data confirmed that medicinal species are widely used whereas the knowledge on edible plants is eroding. The PCA showed four groups of communities, defined by several particular combinations of sociocultural and/or natural variables. Conclusion This comprehensive approach suggests that in general terms the cultural environment has a stronger influence than the natural environment on the use of medicinal and edible plants in rural communities of Cordoba (Argentina). PMID:20003502

Factor structure and dimensionality of the two depression scales in STAR*D using level 1 datasets.

PubMed

Bech, P; Fava, M; Trivedi, M H; Wisniewski, S R; Rush, A J

2011-08-01

The factor structure and dimensionality of the HAM-D(17) and the IDS-C(30) are as yet uncertain, because psychometric analyses of these scales have been performed without a clear separation between factor structure profile and dimensionality (total scores being a sufficient statistic). The first treatment step (Level 1) in the STAR*D study provided a dataset of 4041 outpatients with DSM-IV nonpsychotic major depression. The HAM-D(17) and IDS-C(30) were evaluated by principal component analysis (PCA) without rotation. Mokken analysis tested the unidimensionality of the IDS-C(6), which corresponds to the unidimensional HAM-D(6.) For both the HAM-D(17) and IDS-C(30), PCA identified a bi-directional factor contrasting the depressive symptoms versus the neurovegetative symptoms. The HAM-D(6) and the corresponding IDS-C(6) symptoms all emerged in the depression factor. Both the HAM-D(6) and IDS-C(6) were found to be unidimensional scales, i.e., their total scores are each a sufficient statistic for the measurement of depressive states. STAR*D used only one medication in Level 1. The unidimensional HAM-D(6) and IDS-C(6) should be used when evaluating the pure clinical effect of antidepressive treatment, whereas the multidimensional HAM-D(17) and IDS-C(30) should be considered when selecting antidepressant treatment. Copyright © 2011 Elsevier B.V. All rights reserved.

Network intrusion detection based on a general regression neural network optimized by an improved artificial immune algorithm.

PubMed

Wu, Jianfa; Peng, Dahao; Li, Zhuping; Zhao, Li; Ling, Huanzhang

2015-01-01

To effectively and accurately detect and classify network intrusion data, this paper introduces a general regression neural network (GRNN) based on the artificial immune algorithm with elitist strategies (AIAE). The elitist archive and elitist crossover were combined with the artificial immune algorithm (AIA) to produce the AIAE-GRNN algorithm, with the aim of improving its adaptivity and accuracy. In this paper, the mean square errors (MSEs) were considered the affinity function. The AIAE was used to optimize the smooth factors of the GRNN; then, the optimal smooth factor was solved and substituted into the trained GRNN. Thus, the intrusive data were classified. The paper selected a GRNN that was separately optimized using a genetic algorithm (GA), particle swarm optimization (PSO), and fuzzy C-mean clustering (FCM) to enable a comparison of these approaches. As shown in the results, the AIAE-GRNN achieves a higher classification accuracy than PSO-GRNN, but the running time of AIAE-GRNN is long, which was proved first. FCM and GA-GRNN were eliminated because of their deficiencies in terms of accuracy and convergence. To improve the running speed, the paper adopted principal component analysis (PCA) to reduce the dimensions of the intrusive data. With the reduction in dimensionality, the PCA-AIAE-GRNN decreases in accuracy less and has better convergence than the PCA-PSO-GRNN, and the running speed of the PCA-AIAE-GRNN was relatively improved. The experimental results show that the AIAE-GRNN has a higher robustness and accuracy than the other algorithms considered and can thus be used to classify the intrusive data.

Identification of the isomers using principal component analysis (PCA) method

NASA Astrophysics Data System (ADS)

Kepceoǧlu, Abdullah; Gündoǧdu, Yasemin; Ledingham, Kenneth William David; Kilic, Hamdi Sukur

2016-03-01

In this work, we have carried out a detailed statistical analysis for experimental data of mass spectra from xylene isomers. Principle Component Analysis (PCA) was used to identify the isomers which cannot be distinguished using conventional statistical methods for interpretation of their mass spectra. Experiments have been carried out using a linear TOF-MS coupled to a femtosecond laser system as an energy source for the ionisation processes. We have performed experiments and collected data which has been analysed and interpreted using PCA as a multivariate analysis of these spectra. This demonstrates the strength of the method to get an insight for distinguishing the isomers which cannot be identified using conventional mass analysis obtained through dissociative ionisation processes on these molecules. The PCA results dependending on the laser pulse energy and the background pressure in the spectrometers have been presented in this work.

Measuring disability across cultures — the psychometric properties of the WHODAS II in older people from seven low- and middle-income countries. The 10/66 Dementia Research Group population-based survey

PubMed Central

Sousa, Renata M; Dewey, Michael E; Acosta, Daisy; Jotheeswaran, AT; Castro-Costa, Erico; Ferri, Cleusa P; Guerra, Mariella; Huang, Yueqin; Jacob, KS; Pichardo, Juana Guillermina Rodriguez; Ramírez, Nayeli Garcia; Rodriguez, Juan Llibre; Rodriguez, Marina Calvo; Salas, Aquiles; Sosa, Ana Luisa; Williams, Joseph; Prince, Martin J

2010-01-01

We evaluated the psychometric properties of the 12-item interviewer-administered screener version of the World Health Organization Disability Assessment Schedule – version II (WHODAS II) among older people living in seven low- and middle-income countries. Principal component analysis (PCA), confirmatory factor analysis (CFA) and Mokken analyses were carried out to test for unidimensionality, hierarchical structure, and measurement invariance across 10/66 Dementia Research Group sites. PCA generated a one-factor solution in most sites. In CFA, the two-factor solution generated in Dominican Republic fitted better for all sites other than rural China. The two factors were not easily interpretable, and may have been an artefact of differing item difficulties. Strong internal consistency and high factor loadings for the one-factor solution supported unidimensionality. Furthermore, the WHODAS II was found to be a ‘strong’ Mokken scale. Measurement invariance was supported by the similarity of factor loadings across sites, and by the high between-site correlations in item difficulties. The Mokken results strongly support that the WHODAS II 12-item screener is a unidimensional and hierarchical scale confirming to item response theory (IRT) principles, at least at the monotone homogeneity model level. More work is needed to assess the generalizability of our findings to different populations. Copyright © 2010 John Wiley & Sons, Ltd. PMID:20104493

Cross-validation of the Student Perceptions of Team-Based Learning Scale in the United States.

PubMed

Lein, Donald H; Lowman, John D; Eidson, Christopher A; Yuen, Hon K

2017-01-01

The purpose of this study was to cross-validate the factor structure of the previously developed Student Perceptions of Team-Based Learning (TBL) Scale among students in an entry-level doctor of physical therapy (DPT) program in the United States. Toward the end of the semester in 2 patient/client management courses taught using TBL, 115 DPT students completed the Student Perceptions of TBL Scale, with a response rate of 87%. Principal component analysis (PCA) and confirmatory factor analysis (CFA) were conducted to replicate and confirm the underlying factor structure of the scale. Based on the PCA for the validation sample, the original 2-factor structure (preference for TBL and preference for teamwork) of the Student Perceptions of TBL Scale was replicated. The overall goodness-of-fit indices from the CFA suggested that the original 2-factor structure for the 15 items of the scale demonstrated a good model fit (comparative fit index, 0.95; non-normed fit index/Tucker-Lewis index, 0.93; root mean square error of approximation, 0.06; and standardized root mean square residual, 0.07). The 2 factors demonstrated high internal consistency (alpha= 0.83 and 0.88, respectively). DPT students taught using TBL viewed the factor of preference for teamwork more favorably than preference for TBL. Our findings provide evidence supporting the replicability of the internal structure of the Student Perceptions of TBL Scale when assessing perceptions of TBL among DPT students in patient/client management courses.

Multivariate Statistical Analysis of MSL APXS Bulk Geochemical Data

NASA Astrophysics Data System (ADS)

Hamilton, V. E.; Edwards, C. S.; Thompson, L. M.; Schmidt, M. E.

2014-12-01

We apply cluster and factor analyses to bulk chemical data of 130 soil and rock samples measured by the Alpha Particle X-ray Spectrometer (APXS) on the Mars Science Laboratory (MSL) rover Curiosity through sol 650. Multivariate approaches such as principal components analysis (PCA), cluster analysis, and factor analysis compliment more traditional approaches (e.g., Harker diagrams), with the advantage of simultaneously examining the relationships between multiple variables for large numbers of samples. Principal components analysis has been applied with success to APXS, Pancam, and Mössbauer data from the Mars Exploration Rovers. Factor analysis and cluster analysis have been applied with success to thermal infrared (TIR) spectral data of Mars. Cluster analyses group the input data by similarity, where there are a number of different methods for defining similarity (hierarchical, density, distribution, etc.). For example, without any assumptions about the chemical contributions of surface dust, preliminary hierarchical and K-means cluster analyses clearly distinguish the physically adjacent rock targets Windjana and Stephen as being distinctly different than lithologies observed prior to Curiosity's arrival at The Kimberley. In addition, they are separated from each other, consistent with chemical trends observed in variation diagrams but without requiring assumptions about chemical relationships. We will discuss the variation in cluster analysis results as a function of clustering method and pre-processing (e.g., log transformation, correction for dust cover) and implications for interpreting chemical data. Factor analysis shares some similarities with PCA, and examines the variability among observed components of a dataset so as to reveal variations attributable to unobserved components. Factor analysis has been used to extract the TIR spectra of components that are typically observed in mixtures and only rarely in isolation; there is the potential for similar results with data from APXS. These techniques offer new ways to understand the chemical relationships between the materials interrogated by Curiosity, and potentially their relation to materials observed by APXS instruments on other landed missions.

Prostate cancer gene 3 and multiparametric magnetic resonance can reduce unnecessary biopsies: decision curve analysis to evaluate predictive models.

PubMed

Busetto, Gian Maria; De Berardinis, Ettore; Sciarra, Alessandro; Panebianco, Valeria; Giovannone, Riccardo; Rosato, Stefano; D'Errigo, Paola; Di Silverio, Franco; Gentile, Vincenzo; Salciccia, Stefano

2013-12-01

To overcome the well-known prostate-specific antigen limits, several new biomarkers have been proposed. Since its introduction in clinical practice, the urinary prostate cancer gene 3 (PCA3) assay has shown promising results for prostate cancer (PC) detection. Furthermore, multiparametric magnetic resonance imaging (mMRI) has the ability to better describe several aspects of PC. A prospective study of 171 patients with negative prostate biopsy findings and a persistent high prostate-specific antigen level was conducted to assess the role of mMRI and PCA3 in identifying PC. All patients underwent the PCA3 test and mMRI before a second transrectal ultrasound-guided prostate biopsy. The accuracy and reliability of PCA3 (3 different cutoff points) and mMRI were evaluated. Four multivariate logistic regression models were analyzed, in terms of discrimination and the cost benefit, to assess the clinical role of PCA3 and mMRI in predicting the biopsy outcome. A decision curve analysis was also plotted. Repeated transrectal ultrasound-guided biopsy identified 68 new cases (41.7%) of PC. The sensitivity and specificity of the PCA3 test and mMRI was 68% and 49% and 74% and 90%, respectively. Evaluating the regression models, the best discrimination (area under the curve 0.808) was obtained using the full model (base clinical model plus mMRI and PCA3). The decision curve analysis, to evaluate the cost/benefit ratio, showed good performance in predicting PC with the model that included mMRI and PCA3. mMRI increased the accuracy and sensitivity of the PCA3 test, and the use of the full model significantly improved the cost/benefit ratio, avoiding unnecessary biopsies. Copyright © 2013 Elsevier Inc. All rights reserved.

Prostate Cancer Associated Lipid Signatures in Serum Studied by ESI-Tandem Mass Spectrometryas Potential New Biomarkers.

PubMed

Duscharla, Divya; Bhumireddy, Sudarshana Reddy; Lakshetti, Sridhar; Pospisil, Heike; Murthy, P V L N; Walther, Reinhard; Sripadi, Prabhakar; Ummanni, Ramesh

2016-01-01

Prostate cancer (PCa) is one amongst the most common cancersin western men. Incidence rate ofPCa is on the rise worldwide. The present study deals with theserum lipidome profiling of patients diagnosed with PCa to identify potential new biomarkers. We employed ESI-MS/MS and GC-MS for identification of significantly altered lipids in cancer patient's serum compared to controls. Lipidomic data revealed 24 lipids are significantly altered in cancer patinet's serum (n = 18) compared to normal (n = 18) with no history of PCa. By using hierarchical clustering and principal component analysis (PCA) we could clearly separate cancer patients from control group. Correlation and partition analysis along with Formal Concept Analysis (FCA) have identified that PC (39:6) and FA (22:3) could classify samples with higher certainty. Both the lipids, PC (39:6) and FA (22:3) could influence the cataloging of patients with 100% sensitivity (all 18 control samples are classified correctly) and 77.7% specificity (of 18 tumor samples 4 samples are misclassified) with p-value of 1.612×10-6 in Fischer's exact test. Further, we performed GC-MS to denote fatty acids altered in PCa patients and found that alpha-linolenic acid (ALA) levels are altered in PCa. We also performed an in vitro proliferation assay to determine the effect of ALA in survival of classical human PCa cell lines LNCaP and PC3. We hereby report that the altered lipids PC (39:6) and FA (22:3) offer a new set of biomarkers in addition to the existing diagnostic tests that could significantly improve sensitivity and specificity in PCa diagnosis.

Prostate Cancer Associated Lipid Signatures in Serum Studied by ESI-Tandem Mass Spectrometryas Potential New Biomarkers

PubMed Central

Duscharla, Divya; Bhumireddy, Sudarshana Reddy; Lakshetti, Sridhar; Pospisil, Heike; Murthy, P. V. L. N.; Walther, Reinhard; Sripadi, Prabhakar; Ummanni, Ramesh

2016-01-01

Prostate cancer (PCa) is one amongst the most common cancersin western men. Incidence rate ofPCa is on the rise worldwide. The present study deals with theserum lipidome profiling of patients diagnosed with PCa to identify potential new biomarkers. We employed ESI-MS/MS and GC-MS for identification of significantly altered lipids in cancer patient’s serum compared to controls. Lipidomic data revealed 24 lipids are significantly altered in cancer patinet’s serum (n = 18) compared to normal (n = 18) with no history of PCa. By using hierarchical clustering and principal component analysis (PCA) we could clearly separate cancer patients from control group. Correlation and partition analysis along with Formal Concept Analysis (FCA) have identified that PC (39:6) and FA (22:3) could classify samples with higher certainty. Both the lipids, PC (39:6) and FA (22:3) could influence the cataloging of patients with 100% sensitivity (all 18 control samples are classified correctly) and 77.7% specificity (of 18 tumor samples 4 samples are misclassified) with p-value of 1.612×10−6 in Fischer’s exact test. Further, we performed GC-MS to denote fatty acids altered in PCa patients and found that alpha-linolenic acid (ALA) levels are altered in PCa. We also performed an in vitro proliferation assay to determine the effect of ALA in survival of classical human PCa cell lines LNCaP and PC3. We hereby report that the altered lipids PC (39:6) and FA (22:3) offer a new set of biomarkers in addition to the existing diagnostic tests that could significantly improve sensitivity and specificity in PCa diagnosis. PMID:26958841

Proteomic Comparison and MRM-Based Comparative Analysis of Metabolites Reveal Metabolic Shift in Human Prostate Cancer Cell Lines.

PubMed

Shu, Qingbo; Cai, Tanxi; Chen, Xiulan; Zhu, Helen He; Xue, Peng; Zhu, Nali; Xie, Zhensheng; Wei, Shasha; Zhang, Qing; Niu, Lili; Gao, Wei-Qiang; Yang, Fuquan

2015-08-07

One of the major challenges in prostate cancer therapy remains the development of effective treatments for castration-resistant prostate cancer (CRPC), as the underlying mechanisms for its progression remain elusive. Previous studies showed that androgen receptor (AR) is crucially involved in regulation of metabolism in prostate cancer (PCa) cells throughout the transition from early stage, androgen-sensitive PCa to androgen-independent CRPC. AR achieves such metabolic rewiring directively either via its transcriptional activity or via interactions with AMP-activated protein kinase (AMPK). However, due to the heterogeneous expression and activity status of AR in PCa cells, it remains a challenge to investigate the links between AR status and metabolic alterations. To this end, we compared the proteomes of three pairs of androgen-sensitive (AS) and androgen-independent (AI) PCa cell lines, namely, PC3-AR(+)/PC3, 22Rv1/Du145, and LNCaP/C42B, using an iTRAQ labeling approach. Our results revealed that most of the differentially expressed proteins between each pair function in metabolism, indicating a metabolic shift between AS and AI cells, as further validated by multiple reaction monitoring (MRM)-based quantification of nucleotides and relative comparison of fatty acids between these cell lines. Furthermore, increased adenylate kinase isoenzyme 1 (AK1) in AS relative to AI cells may result in activation of AMPK, representing a major regulatory factor involved in the observed metabolic shift in PCa cells.

Principal component analysis of socioeconomic factors and their association with malaria and arbovirus risk in Tanzania: a sensitivity analysis.

PubMed

Homenauth, Esha; Kajeguka, Debora; Kulkarni, Manisha A

2017-11-01

Principal component analysis (PCA) is frequently adopted for creating socioeconomic proxies in order to investigate the independent effects of wealth on disease status. The guidelines and methods for the creation of these proxies are well described and validated. The Demographic and Health Survey, World Health Survey and the Living Standards Measurement Survey are examples of large data sets that use PCA to create wealth indices particularly in low and middle-income countries (LMIC), where quantifying wealth-disease associations is problematic due to the unavailability of reliable income and expenditure data. However, the application of this method to smaller survey data sets, especially in rural LMIC settings, is less rigorously studied.In this paper, we aimed to highlight some of these issues by investigating the association of derived wealth indices using PCA on risk of vector-borne disease infection in Tanzania focusing on malaria and key arboviruses (ie, dengue and chikungunya). We demonstrated that indices consisting of subsets of socioeconomic indicators provided the least methodologically flawed representations of household wealth compared with an index that combined all socioeconomic variables. These results suggest that the choice of the socioeconomic indicators included in a wealth proxy can influence the relative position of households in the overall wealth hierarchy, and subsequently the strength of disease associations. This can, therefore, influence future resource planning activities and should be considered among investigators who use a PCA-derived wealth index based on community-level survey data to influence programme or policy decisions in rural LMIC settings. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Racial Differences in the Diagnosis and Treatment of Prostate Cancer.

PubMed

Pietro, Giuliano Di; Chornokur, Ganna; Kumar, Nagi B; Davis, Chemar; Park, Jong Y

2016-11-01

Disparities between African American and Caucasian men in prostate cancer (PCa) diagnosis and treatment in the United States have been well established, with significant racial disparities documented at all stages of PCa management, from differences in the type of treatment offered to progression-free survival or death. These disparities appear to be complex in nature, involving biological determinants as well as socioeconomic and cultural aspects. We present a review of the literature on racial disparities in the diagnosis of PCa, treatment, survival, and genetic susceptibility. Significant differences were found among African Americans and whites in the incidence and mortality rates; namely, African Americans are diagnosed with PCa at younger ages than whites and usually with more advanced stages of the disease, and also undergo prostate-specific antigen testing less frequently. However, the determinants of the high rate of incidence and aggressiveness of PCa in African Americans remain unresolved. This pattern can be attributed to socioeconomic status, detection occurring at advanced stages of the disease, biological aggressiveness, family history, and differences in genetic susceptibility. Another risk factor for PCa is obesity. We found many discrepancies regarding treatment, including a tendency for more African American patients to be in watchful waiting than whites. Many factors are responsible for the higher incidence and mortality rates in African Americans. Better screening, improved access to health insurance and clinics, and more homogeneous forms of treatment will contribute to the reduction of disparities between African Americans and white men in PCa incidence and mortality.

Accumulation of heavy metals and trace elements in fluvial sediments received effluents from traditional and semiconductor industries

PubMed Central

Hsu, Liang-Ching; Huang, Ching-Yi; Chuang, Yen-Hsun; Chen, Ho-Wen; Chan, Ya-Ting; Teah, Heng Yi; Chen, Tsan-Yao; Chang, Chiung-Fen; Liu, Yu-Ting; Tzou, Yu-Min

2016-01-01

Metal accumulation in sediments threatens adjacent ecosystems due to the potential of metal mobilization and the subsequent uptake into food webs. Here, contents of heavy metals (Cd, Cr, Cu, Ni, Pb, and Zn) and trace elements (Ga, In, Mo, and Se) were determined for river waters and bed sediments that received sewage discharged from traditional and semiconductor industries. We used principal component analysis (PCA) to determine the metal distribution in relation to environmental factors such as pH, EC, and organic matter (OM) contents in the river basin. While water PCA categorized discharged metals into three groups that implied potential origins of contamination, sediment PCA only indicated a correlation between metal accumulation and OM contents. Such discrepancy in metal distribution between river water and bed sediment highlighted the significance of physical-chemical properties of sediment, especially OM, in metal retention. Moreover, we used Se XANES as an example to test the species transformation during metal transportation from effluent outlets to bed sediments and found a portion of Se inventory shifted from less soluble elemental Se to the high soluble and toxic selenite and selenate. The consideration of environmental factors is required to develop pollution managements and assess environmental risks for bed sediments. PMID:27681994

Accumulation of heavy metals and trace elements in fluvial sediments received effluents from traditional and semiconductor industries.

PubMed

Hsu, Liang-Ching; Huang, Ching-Yi; Chuang, Yen-Hsun; Chen, Ho-Wen; Chan, Ya-Ting; Teah, Heng Yi; Chen, Tsan-Yao; Chang, Chiung-Fen; Liu, Yu-Ting; Tzou, Yu-Min

2016-09-29

Metal accumulation in sediments threatens adjacent ecosystems due to the potential of metal mobilization and the subsequent uptake into food webs. Here, contents of heavy metals (Cd, Cr, Cu, Ni, Pb, and Zn) and trace elements (Ga, In, Mo, and Se) were determined for river waters and bed sediments that received sewage discharged from traditional and semiconductor industries. We used principal component analysis (PCA) to determine the metal distribution in relation to environmental factors such as pH, EC, and organic matter (OM) contents in the river basin. While water PCA categorized discharged metals into three groups that implied potential origins of contamination, sediment PCA only indicated a correlation between metal accumulation and OM contents. Such discrepancy in metal distribution between river water and bed sediment highlighted the significance of physical-chemical properties of sediment, especially OM, in metal retention. Moreover, we used Se XANES as an example to test the species transformation during metal transportation from effluent outlets to bed sediments and found a portion of Se inventory shifted from less soluble elemental Se to the high soluble and toxic selenite and selenate. The consideration of environmental factors is required to develop pollution managements and assess environmental risks for bed sediments.

Accumulation of heavy metals and trace elements in fluvial sediments received effluents from traditional and semiconductor industries

NASA Astrophysics Data System (ADS)

Hsu, Liang-Ching; Huang, Ching-Yi; Chuang, Yen-Hsun; Chen, Ho-Wen; Chan, Ya-Ting; Teah, Heng Yi; Chen, Tsan-Yao; Chang, Chiung-Fen; Liu, Yu-Ting; Tzou, Yu-Min

2016-09-01

Metal accumulation in sediments threatens adjacent ecosystems due to the potential of metal mobilization and the subsequent uptake into food webs. Here, contents of heavy metals (Cd, Cr, Cu, Ni, Pb, and Zn) and trace elements (Ga, In, Mo, and Se) were determined for river waters and bed sediments that received sewage discharged from traditional and semiconductor industries. We used principal component analysis (PCA) to determine the metal distribution in relation to environmental factors such as pH, EC, and organic matter (OM) contents in the river basin. While water PCA categorized discharged metals into three groups that implied potential origins of contamination, sediment PCA only indicated a correlation between metal accumulation and OM contents. Such discrepancy in metal distribution between river water and bed sediment highlighted the significance of physical-chemical properties of sediment, especially OM, in metal retention. Moreover, we used Se XANES as an example to test the species transformation during metal transportation from effluent outlets to bed sediments and found a portion of Se inventory shifted from less soluble elemental Se to the high soluble and toxic selenite and selenate. The consideration of environmental factors is required to develop pollution managements and assess environmental risks for bed sediments.

A stock market forecasting model combining two-directional two-dimensional principal component analysis and radial basis function neural network.

PubMed

Guo, Zhiqiang; Wang, Huaiqing; Yang, Jie; Miller, David J

2015-01-01

In this paper, we propose and implement a hybrid model combining two-directional two-dimensional principal component analysis ((2D)2PCA) and a Radial Basis Function Neural Network (RBFNN) to forecast stock market behavior. First, 36 stock market technical variables are selected as the input features, and a sliding window is used to obtain the input data of the model. Next, (2D)2PCA is utilized to reduce the dimension of the data and extract its intrinsic features. Finally, an RBFNN accepts the data processed by (2D)2PCA to forecast the next day's stock price or movement. The proposed model is used on the Shanghai stock market index, and the experiments show that the model achieves a good level of fitness. The proposed model is then compared with one that uses the traditional dimension reduction method principal component analysis (PCA) and independent component analysis (ICA). The empirical results show that the proposed model outperforms the PCA-based model, as well as alternative models based on ICA and on the multilayer perceptron.

A Stock Market Forecasting Model Combining Two-Directional Two-Dimensional Principal Component Analysis and Radial Basis Function Neural Network

PubMed Central

Guo, Zhiqiang; Wang, Huaiqing; Yang, Jie; Miller, David J.

2015-01-01

In this paper, we propose and implement a hybrid model combining two-directional two-dimensional principal component analysis ((2D)2PCA) and a Radial Basis Function Neural Network (RBFNN) to forecast stock market behavior. First, 36 stock market technical variables are selected as the input features, and a sliding window is used to obtain the input data of the model. Next, (2D)2PCA is utilized to reduce the dimension of the data and extract its intrinsic features. Finally, an RBFNN accepts the data processed by (2D)2PCA to forecast the next day's stock price or movement. The proposed model is used on the Shanghai stock market index, and the experiments show that the model achieves a good level of fitness. The proposed model is then compared with one that uses the traditional dimension reduction method principal component analysis (PCA) and independent component analysis (ICA). The empirical results show that the proposed model outperforms the PCA-based model, as well as alternative models based on ICA and on the multilayer perceptron. PMID:25849483

Procoagulant activity of extracellular vesicles as a potential biomarker for risk of thrombosis and DIC in patients with acute leukaemia.

PubMed

Gheldof, Damien; Haguet, Hélène; Dogné, Jean-Michel; Bouvy, Céline; Graux, Carlos; George, Fabienne; Sonet, Anne; Chatelain, Christian; Chatelain, Bernard; Mullier, François

2017-02-01

Haemostatic complication is common for patients with hematologic malignancies. Recent studies suggest that the procoagulant activity (PCA) of extracellular vesicles (EV) may play a major role in venous thromboembolism and disseminated intravascular coagulation (DIC) in acute leukaemia. To study the impact of EVs from leukaemic patients on thrombin generation and to assess EV-PCA as a potential biomarker for thrombotic complications in patients with acute leukaemia. Blood samples from a cohort of patients with newly diagnosed acute leukaemia were obtained before treatment (D-0), 3 and 7 days after treatment (D-3 and D-7). Extracellular vesicles were isolated and concentrated by ultracentrifugation. EV-PCA was assessed by thrombin generation assay, and EV-associated tissue factor activity was measured using a commercial bio-immunoassay (Zymuphen MP-TF®). Of the 53 patients, 6 had increased EV-PCA at D-0 and 4 had a thrombotic event. Patients without thrombotic events (n = 47) had no elevated EV-PCA. One patient had increased EVs with procoagulant activity at D-3 and developed a DIC at D-5. This patient had no increased EVs-related tissue factor activity from D-0 to D-7 (<2 pg/ml). Eight patients had increased EVs with tissue factor activity (>2 pg/ml), of these, four had a thrombosis and two had haemorrhages. Procoagulant activity of extracellular vesicles could have a predictive value in excluding the risk of thrombotic events. Our findings also suggest a possible association between thrombotic events and EV-PCA.

Survival outcomes of radical prostatectomy and external beam radiotherapy in clinically localized high-risk prostate cancer: a population-based, propensity score matched study

PubMed Central

Gu, Xiaobin; Gao, Xianshu; Cui, Ming; Xie, Mu; Ma, Mingwei; Qin, Shangbin; Li, Xiaoying; Qi, Xin; Bai, Yun; Wang, Dian

2018-01-01

Objective This study was aimed to compare survival outcomes in high-risk prostate cancer (PCa) patients receiving external beam radiotherapy (EBRT) or radical prostatectomy (RP). Materials and methods The Surveillance, Epidemiology, and End Results (SEER) database was used to identify PCa patients with high-risk features who received RP alone or EBRT alone from 2004 to 2008. Propensity-score matching (PSM) was performed. Kaplan–Meier survival analysis was used to compare cancer-specific survival (CSS) and overall survival (OS). Multivariate Cox regression analysis was used to identify independent prognostic factors. Results A total of 24,293 patients were identified, 14,460 patients receiving RP and 9833 patients receiving EBRT. Through PSM, 3828 patients were identified in each group. The mean CSS was 128.6 and 126.7 months for RP and EBRT groups, respectively (P<0.001). The subgroup analyses showed that CSS of the RP group was better than that of the EBRT group for patients aged <65 years (P<0.001), White race (P<0.001), and married status (P<0.001). However, there was no significant difference in CSS for patients aged ≥65 years, Black race, other race, and unmarried status. Similar trends were observed for OS. Multivariate analysis showed that EBRT treatment modality, T3–T4 stage, Gleason score 8–10, and prostate-specific antigen >20 ng/mL were significant risk factors for both CSS and OS. Conclusion This study suggested that survival outcomes might be better with RP than EBRT in high-risk PCa patients aged <65 years; however, RP and EBRT provided equivalent survival outcomes in older patients, which argues for primary radiotherapy in this older cohort.

Proton Nuclear Magnetic Resonance-Spectroscopic Discrimination of Wines Reflects Genetic Homology of Several Different Grape (V. vinifera L.) Cultivars.

PubMed

Hu, Boran; Yue, Yaqing; Zhu, Yong; Wen, Wen; Zhang, Fengmin; Hardie, Jim W

2015-01-01

Proton nuclear magnetic resonance spectroscopy coupled multivariate analysis (1H NMR-PCA/PLS-DA) is an important tool for the discrimination of wine products. Although 1H NMR has been shown to discriminate wines of different cultivars, a grape genetic component of the discrimination has been inferred only from discrimination of cultivars of undefined genetic homology and in the presence of many confounding environmental factors. We aimed to confirm the influence of grape genotypes in the absence of those factors. We applied 1H NMR-PCA/PLS-DA and hierarchical cluster analysis (HCA) to wines from five, variously genetically-related grapevine (V. vinifera) cultivars; all grown similarly on the same site and vinified similarly. We also compared the semi-quantitative profiles of the discriminant metabolites of each cultivar with previously reported chemical analyses. The cultivars were clearly distinguishable and there was a general correlation between their grouping and their genetic homology as revealed by recent genomic studies. Between cultivars, the relative amounts of several of the cultivar-related discriminant metabolites conformed closely with reported chemical analyses. Differences in grape-derived metabolites associated with genetic differences alone are a major source of 1H NMR-based discrimination of wines and 1H NMR has the capacity to discriminate between very closely related cultivars. The study confirms that genetic variation among grape cultivars alone can account for the discrimination of wine by 1H NMR-PCA/PLS and indicates that 1H NMR spectra of wine of single grape cultivars may in future be used in tandem with hierarchical cluster analysis to elucidate genetic lineages and metabolomic relations of grapevine cultivars. In the absence of genetic information, for example, where predecessor varieties are no longer extant, this may be a particularly useful approach.

Identification and classification of upper limb motions using PCA.

PubMed

Veer, Karan; Vig, Renu

2018-03-28

This paper describes the utility of principal component analysis (PCA) in classifying upper limb signals. PCA is a powerful tool for analyzing data of high dimension. Here, two different input strategies were explored. The first method uses upper arm dual-position-based myoelectric signal acquisition and the other solely uses PCA for classifying surface electromyogram (SEMG) signals. SEMG data from the biceps and the triceps brachii muscles and four independent muscle activities of the upper arm were measured in seven subjects (total dataset=56). The datasets used for the analysis are rotated by class-specific principal component matrices to decorrelate the measured data prior to feature extraction.

Integrated analysis of epigenomic and genomic changes by DNA methylation dependent mechanisms provides potential novel biomarkers for prostate cancer.

PubMed

White-Al Habeeb, Nicole M A; Ho, Linh T; Olkhov-Mitsel, Ekaterina; Kron, Ken; Pethe, Vaijayanti; Lehman, Melanie; Jovanovic, Lidija; Fleshner, Neil; van der Kwast, Theodorus; Nelson, Colleen C; Bapat, Bharati

2014-09-15

Epigenetic silencing mediated by CpG methylation is a common feature of many cancers. Characterizing aberrant DNA methylation changes associated with tumor progression may identify potential prognostic markers for prostate cancer (PCa). We treated two PCa cell lines, 22Rv1 and DU-145 with the demethylating agent 5-Aza 2'-deoxycitidine (DAC) and global methylation status was analyzed by performing methylation-sensitive restriction enzyme based differential methylation hybridization strategy followed by genome-wide CpG methylation array profiling. In addition, we examined gene expression changes using a custom microarray. Gene Set Enrichment Analysis (GSEA) identified the most significantly dysregulated pathways. In addition, we assessed methylation status of candidate genes that showed reduced CpG methylation and increased gene expression after DAC treatment, in Gleason score (GS) 8 vs. GS6 patients using three independent cohorts of patients; the publically available The Cancer Genome Atlas (TCGA) dataset, and two separate patient cohorts. Our analysis, by integrating methylation and gene expression in PCa cell lines, combined with patient tumor data, identified novel potential biomarkers for PCa patients. These markers may help elucidate the pathogenesis of PCa and represent potential prognostic markers for PCa patients.

The impact of moderate wine consumption on the risk of developing prostate cancer

PubMed Central

Ferro, Matteo; Foerster, Beat; Abufaraj, Mohammad; Briganti, Alberto; Karakiewicz, Pierre I; Shariat, Shahrokh F

2018-01-01

Objective To investigate the impact of moderate wine consumption on the risk of prostate cancer (PCa). We focused on the differential effect of moderate consumption of red versus white wine. Design This study was a meta-analysis that includes data from case–control and cohort studies. Materials and methods A systematic search of Web of Science, Medline/PubMed, and Cochrane library was performed on December 1, 2017. Studies were deemed eligible if they assessed the risk of PCa due to red, white, or any wine using multivariable logistic regression analysis. We performed a formal meta-analysis for the risk of PCa according to moderate wine and wine type consumption (white or red). Heterogeneity between studies was assessed using Cochrane’s Q test and I2 statistics. Publication bias was assessed using Egger’s regression test. Results A total of 930 abstracts and titles were initially identified. After removal of duplicates, reviews, and conference abstracts, 83 full-text original articles were screened. Seventeen studies (611,169 subjects) were included for final evaluation and fulfilled the inclusion criteria. In the case of moderate wine consumption: the pooled risk ratio (RR) for the risk of PCa was 0.98 (95% CI 0.92–1.05, p=0.57) in the multivariable analysis. Moderate white wine consumption increased the risk of PCa with a pooled RR of 1.26 (95% CI 1.10–1.43, p=0.001) in the multi-variable analysis. Meanwhile, moderate red wine consumption had a protective role reducing the risk by 12% (RR 0.88, 95% CI 0.78–0.999, p=0.047) in the multivariable analysis that comprised 222,447 subjects. Conclusions In this meta-analysis, moderate wine consumption did not impact the risk of PCa. Interestingly, regarding the type of wine, moderate consumption of white wine increased the risk of PCa, whereas moderate consumption of red wine had a protective effect. Further analyses are needed to assess the differential molecular effect of white and red wine conferring their impact on PCa risk. PMID:29713200

Visible micro-Raman spectroscopy of single human mammary epithelial cells exposed to x-ray radiation.

PubMed

Delfino, Ines; Perna, Giuseppe; Lasalvia, Maria; Capozzi, Vito; Manti, Lorenzo; Camerlingo, Carlo; Lepore, Maria

2015-03-01

A micro-Raman spectroscopy investigation has been performed in vitro on single human mammary epithelial cells after irradiation by graded x-ray doses. The analysis by principal component analysis (PCA) and interval-PCA (i-PCA) methods has allowed us to point out the small differences in the Raman spectra induced by irradiation. This experimental approach has enabled us to delineate radiation-induced changes in protein, nucleic acid, lipid, and carbohydrate content. In particular, the dose dependence of PCA and i-PCA components has been analyzed. Our results have confirmed that micro-Raman spectroscopy coupled to properly chosen data analysis methods is a very sensitive technique to detect early molecular changes at the single-cell level following exposure to ionizing radiation. This would help in developing innovative approaches to monitor radiation cancer radiotherapy outcome so as to reduce the overall radiation dose and minimize damage to the surrounding healthy cells, both aspects being of great importance in the field of radiation therapy.

Whole milk intake is associated with prostate cancer-specific mortality among U.S. male physicians.

PubMed

Song, Yan; Chavarro, Jorge E; Cao, Yin; Qiu, Weiliang; Mucci, Lorelei; Sesso, Howard D; Stampfer, Meir J; Giovannucci, Edward; Pollak, Michael; Liu, Simin; Ma, Jing

2013-02-01

Previous studies have associated higher milk intake with greater prostate cancer (PCa) incidence, but little data are available concerning milk types and the relation between milk intake and risk of fatal PCa. We investigated the association between intake of dairy products and the incidence and survival of PCa during a 28-y follow-up. We conducted a cohort study in the Physicians' Health Study (n = 21,660) and a survival analysis among the incident PCa cases (n = 2806). Information on dairy product consumption was collected at baseline. PCa cases and deaths (n = 305) were confirmed during follow-up. The intake of total dairy products was associated with increased PCa incidence [HR = 1.12 (95% CI: 0.93, 1.35); >2.5 servings/d vs. ≤0.5 servings/d]. Skim/low-fat milk intake was positively associated with risk of low-grade, early stage, and screen-detected cancers, whereas whole milk intake was associated only with fatal PCa [HR = 1.49 (95% CI: 0.97, 2.28); ≥237 mL/d (1 serving/d) vs. rarely consumed]. In the survival analysis, whole milk intake remained associated with risk of progression to fatal disease after diagnosis [HR = 2.17 (95% CI: 1.34, 3.51)]. In this prospective cohort, higher intake of skim/low-fat milk was associated with a greater risk of nonaggressive PCa. Most importantly, only whole milk was consistently associated with higher incidence of fatal PCa in the entire cohort and higher PCa-specific mortality among cases. These findings add further evidence to suggest the potential role of dairy products in the development and prognosis of PCa.

Activation of Beta-Catenin Signaling in Androgen Receptor–Negative Prostate Cancer Cells

PubMed Central

Wan, Xinhai; Liu, Jie; Lu, Jing-Fang; Tzelepi, Vassiliki; Yang, Jun; Starbuck, Michael W.; Diao, Lixia; Wang, Jing; Efstathiou, Eleni; Vazquez, Elba S.; Troncoso, Patricia; Maity, Sankar N.; Navone, Nora M.

2012-01-01

Purpose To study Wnt/beta-catenin in castrate-resistant prostate cancer (CRPC) and understand its function independently of the beta-catenin–androgen receptor (AR) interaction. Experimental Design We performed beta-catenin immunocytochemical analysis, evaluated TOP-flash reporter activity (a reporter of beta-catenin–mediated transcription), and sequenced the beta-catenin gene in MDA PCa 118a, MDA PCa 118b, MDA PCa 2b, and PC-3 prostate cancer (PCa) cells. We knocked down beta-catenin in AR-negative MDA PCa 118b cells and performed comparative gene-array analysis. We also immunohistochemically analyzed beta-catenin and AR in 27 bone metastases of human CRPCs. Results Beta-catenin nuclear accumulation and TOP-flash reporter activity were high in MDA PCa 118b but not in MDA PCa 2b or PC-3 cells. MDA PCa 118a and 118b cells carry a mutated beta-catenin at codon 32 (D32G). Ten genes were expressed differently (false discovery rate, 0.05) in MDA PCa 118b cells with downregulated beta-catenin. One such gene, hyaluronan synthase 2 (HAS2), synthesizes hyaluronan, a core component of the extracellular matrix. We confirmed HAS2 upregulation in PC-3 cells transfected with D32G-mutant beta-catenin. Finally, we found nuclear localization of beta-catenin in 10 of 27 human tissue specimens; this localization was inversely associated with AR expression (P = 0.056, Fisher’s exact test), suggesting that reduced AR expression enables Wnt/beta-catenin signaling. Conclusion We identified a previously unknown downstream target of beta-catenin, HAS2, in PCa, and found that high beta-catenin nuclear localization and low or no AR expression may define a subpopulation of men with bone-metastatic PCa. These findings may guide physicians in managing these patients. PMID:22298898

Combinations of elevated tissue miRNA-17-92 cluster expression and serum prostate-specific antigen as potential diagnostic biomarkers for prostate cancer.

PubMed

Feng, Sujuan; Qian, Xiaosong; Li, Han; Zhang, Xiaodong

2017-12-01

The aim of the present study was to investigate the effectiveness of the miR-17-92 cluster as a disease progression marker in prostate cancer (PCa). Reverse transcription-quantitative polymerase chain reaction analysis was used to detect the microRNA (miR)-17-92 cluster expression levels in tissues from patients with PCa or benign prostatic hyperplasia (BPH), in addition to in PCa and BPH cell lines. Spearman correlation was used for comparison and estimation of correlations between miRNA expression levels and clinicopathological characteristics such as the Gleason score and prostate-specific antigen (PSA). Receiver operating curve (ROC) analysis was performed for evaluation of specificity and sensitivity of miR-17-92 cluster expression levels for discriminating patients with PCa from patients with BPH. Kaplan-Meier analysis was plotted to investigate the predictive potential of miR-17-92 cluster for PCa biochemical recurrence. Expression of the majority of miRNAs in the miR-17-92 cluster was identified to be significantly increased in PCa tissues and cell lines. Bivariate correlation analysis indicated that the high expression of unregulated miRNAs was positively correlated with Gleason grade, but had no significant association with PSA. ROC curves demonstrated that high expression of miR-17-92 cluster predicted a higher diagnostic accuracy compared with PSA. Improved discriminating quotients were observed when combinations of unregulated miRNAs with PSA were used. Survival analysis confirmed a high combined miRNA score of miR-17-92 cluster was associated with shorter biochemical recurrence interval. miR-17-92 cluster could be a potential diagnostic and prognostic biomarker for PCa, and the combination of the miR-17-92 cluster and serum PSA may enhance the accuracy for diagnosis of PCa.

Classification of narcotics in solid mixtures using principal component analysis and Raman spectroscopy.

PubMed

Ryder, Alan G

2002-03-01

Eighty-five solid samples consisting of illegal narcotics diluted with several different materials were analyzed by near-infrared (785 nm excitation) Raman spectroscopy. Principal Component Analysis (PCA) was employed to classify the samples according to narcotic type. The best sample discrimination was obtained by using the first derivative of the Raman spectra. Furthermore, restricting the spectral variables for PCA to 2 or 3% of the original spectral data according to the most intense peaks in the Raman spectrum of the pure narcotic resulted in a rapid discrimination method for classifying samples according to narcotic type. This method allows for the easy discrimination between cocaine, heroin, and MDMA mixtures even when the Raman spectra are complex or very similar. This approach of restricting the spectral variables also decreases the computational time by a factor of 30 (compared to the complete spectrum), making the methodology attractive for rapid automatic classification and identification of suspect materials.

Decreased expression of serine protease inhibitor family G1 (SERPING1) in prostate cancer can help distinguish high-risk prostate cancer and predicts malignant progression.

PubMed

Peng, Shengmeng; Du, Tao; Wu, Wanhua; Chen, Xianju; Lai, Yiming; Zhu, Dingjun; Wang, Qiong; Ma, Xiaoming; Lin, Chunhao; Li, Zean; Guo, Zhenghui; Huang, Hai

2018-06-11

The aim of this study was to investigate the associations of serine proteinase inhibitor family G1 (SERPING1) down-regulation with poor prognosis in patients with prostate cancer (PCa). Furthermore, we aim to find more novel and effective PCa molecular markers to provide an early screening of PCa, distinguish patients with aggressive PCa, predict the prognosis, or reduce the economic burden of PCa. SERPING1 protein expression in both human PCa and normal prostate tissues was detected by immunohistochemical staining, which intensity was analyzed in association with clinical pathological parameters such Gleason score, pathological grade, clinical stage, tumor stage, lymph node metastasis, and distant metastasis. Moreover, we used The Cancer Genome Atlas (TCGA) Database, Taylor Database, and Oncomine dataset to validate our immunohistochemical results and investigated the value of SERPING1 in PCa at mRNA level. Kaplan-Meier analysis and Cox regression analysis were performed to evaluate the relationship between SERPING1 and prognosis of patients with PCa. The outcome showed that SERPING1 was expressed mainly in cytoplasm of grand cells of prostate tissue and was significantly expressed less in PCa (P<0.001). Furthermore, in the tissue microarray of our samples, decreasing expression of SERPING1 was correlated with the higher Gleason score (P = 0.004), the higher pathological grade (P = 0.01) and the advanced tumor stage (P = 0.005) at protein level. In TCGA dataset and Taylor Dataset, low-expressed SERPING1 was correlated with the younger patient (P = 0.02 in TCGA, P = 0.044 in Taylor) and the higher Gleason score (P = 0.019 in TCGA, P<0.001 in Taylor) at mRNA level. Kaplan-Meier analysis revealed that the lower mRNA of SERPING1 predicted lower overall survivals (P = 0.027 in TCGA), lower disease-free survival (P = 0.029) and lower biochemical recurrence-free survival (P = 0.011 in Taylor). Data from Oncomine database shown that SERPING1 low expression implying higher malignancy of prostate lesions. Using multivariate analysis, we also found that SERPING1 expression was independent prognostic marker of poor disease-free survival and biochemical recurrence-free survival. SERPING1 may play an important role in PCa and can be serve as a novel marker in diagnosis and prognostic prediction in PCa. In addition, levels of SERPING1 can help identify low-risk prostate to provide reference for patients with PCa to accept active surveillance and reduce overtreatment. Copyright © 2018 Elsevier Inc. All rights reserved.

Predicting prostate biopsy outcome: prostate health index (phi) and prostate cancer antigen 3 (PCA3) are useful biomarkers.

PubMed

Ferro, Matteo; Bruzzese, Dario; Perdonà, Sisto; Mazzarella, Claudia; Marino, Ada; Sorrentino, Alessandra; Di Carlo, Angelina; Autorino, Riccardo; Di Lorenzo, Giuseppe; Buonerba, Carlo; Altieri, Vincenzo; Mariano, Angela; Macchia, Vincenzo; Terracciano, Daniela

2012-08-16

Indication for prostate biopsy is presently mainly based on prostate-specific antigen (PSA) serum levels and digital-rectal examination (DRE). In view of the unsatisfactory accuracy of these two diagnostic exams, research has focused on novel markers to improve pre-biopsy prostate cancer detection, such as phi and PCA3. The purpose of this prospective study was to assess the diagnostic accuracy of phi and PCA3 for prostate cancer using biopsy as gold standard. Phi index (Beckman coulter immunoassay), PCA3 score (Progensa PCA3 assay) and other established biomarkers (tPSA, fPSA and %fPSA) were assessed before a 18-core prostate biopsy in a group of 251 subjects at their first biopsy. Values of %p2PSA and phi were significantly higher in patients with PCa compared with PCa-negative group (p<0.001) and also compared with high grade prostatic intraepithelial neoplasia (HGPIN) (p<0.001). PCA3 score values were significantly higher in PCa compared with PCa-negative subjects (p<0.001) and in HGPIN vs PCa-negative patients (p<0.001). ROC curve analysis showed that %p2PSA, phi and PCA3 are predictive of malignancy. In conclusion, %p2PSA, phi and PCA3 may predict a diagnosis of PCa in men undergoing their first prostate biopsy. PCA3 score is more useful in discriminating between HGPIN and non-cancer. Copyright © 2012 Elsevier B.V. All rights reserved.

Tuberculosis and poverty: why are the poor at greater risk in India?

PubMed

Oxlade, Olivia; Murray, Megan

2012-01-01

Although poverty is widely recognized as an important risk factor for tuberculosis (TB) disease, the specific proximal risk factors that mediate this association are less clear. The objective of our study was to investigate the mechanisms by which poverty increases the risk of TB. Using individual level data from 198,754 people from the 2006 Demographic Health Survey (DHS) for India, we assessed self-reported TB status, TB determinants and household socioeconomic status. We used these data to calculate the population attributable fractions (PAF) for each key TB risk factor based on the prevalence of determinants and estimates of the effect of these risk factors derived from published sources. We conducted a mediation analysis using principal components analysis (PCA) and regression to demonstrate how the association between poverty and TB prevalence is mediated. The prevalence of self-reported TB in the 2006 DHS for India was 545 per 100,000 and ranged from 201 in the highest quintile to 1100 in the lowest quintile. Among those in the poorest population, the PAFs for low body mass index (BMI) and indoor air pollution were 34.2% and 28.5% respectively. The PCA analysis also showed that low BMI had the strongest mediating effect on the association between poverty and prevalent TB (12%, p = 0.019). TB control strategies should be targeted to the poorest populations that are most at risk, and should address the most important determinants of disease--specifically low BMI and indoor air pollution.

PCA as a practical indicator of OPLS-DA model reliability.

PubMed

Worley, Bradley; Powers, Robert

Principal Component Analysis (PCA) and Orthogonal Projections to Latent Structures Discriminant Analysis (OPLS-DA) are powerful statistical modeling tools that provide insights into separations between experimental groups based on high-dimensional spectral measurements from NMR, MS or other analytical instrumentation. However, when used without validation, these tools may lead investigators to statistically unreliable conclusions. This danger is especially real for Partial Least Squares (PLS) and OPLS, which aggressively force separations between experimental groups. As a result, OPLS-DA is often used as an alternative method when PCA fails to expose group separation, but this practice is highly dangerous. Without rigorous validation, OPLS-DA can easily yield statistically unreliable group separation. A Monte Carlo analysis of PCA group separations and OPLS-DA cross-validation metrics was performed on NMR datasets with statistically significant separations in scores-space. A linearly increasing amount of Gaussian noise was added to each data matrix followed by the construction and validation of PCA and OPLS-DA models. With increasing added noise, the PCA scores-space distance between groups rapidly decreased and the OPLS-DA cross-validation statistics simultaneously deteriorated. A decrease in correlation between the estimated loadings (added noise) and the true (original) loadings was also observed. While the validity of the OPLS-DA model diminished with increasing added noise, the group separation in scores-space remained basically unaffected. Supported by the results of Monte Carlo analyses of PCA group separations and OPLS-DA cross-validation metrics, we provide practical guidelines and cross-validatory recommendations for reliable inference from PCA and OPLS-DA models.

ToF-SIMS PCA analysis of Myrtus communis L.

NASA Astrophysics Data System (ADS)

Piras, F. M.; Dettori, M. F.; Magnani, A.

2009-06-01

Nowadays there is a growing interest of researchers for the application of sophisticated analytical techniques in conjunction with statistical data analysis methods to the characterization of natural products to assure their authenticity and quality, and for the possibility of direct analysis of food to obtain maximum information. In this work, time-of-flight secondary ion mass spectrometry (ToF-SIMS) in conjunction with principal components analysis (PCA) are applied to study the chemical composition and variability of Sardinian myrtle ( Myrtus communis L.) through the analysis of both berries alcoholic extracts and berries epicarp. ToF-SIMS spectra of berries epicarp show that the epicuticular waxes consist mainly of carboxylic acids with chain length ranging from C20 to C30, or identical species formed from fragmentation of long-chain esters. PCA of ToF-SIMS data from myrtle berries epicarp distinguishes two groups characterized by a different surface concentration of triacontanoic acid. Variability in antocyanins, flavonols, α-tocopherol, and myrtucommulone contents is showed by ToF-SIMS PCA analysis of myrtle berries alcoholic extracts.

New approach for rapid assessment of trophic status of Yellow Sea and East China Sea using easy-to-measure parameters

NASA Astrophysics Data System (ADS)

Kong, Xianyu; Liu, Yanfang; Jian, Huimin; Su, Rongguo; Yao, Qingzhen; Shi, Xiaoyong

2017-10-01

To realize potential cost savings in coastal monitoring programs and provide timely advice for marine management, there is an urgent need for efficient evaluation tools based on easily measured variables for the rapid and timely assessment of estuarine and offshore eutrophication. In this study, using parallel factor analysis (PARAFAC), principal component analysis (PCA), and discriminant function analysis (DFA) with the trophic index (TRIX) for reference, we developed an approach for rapidly assessing the eutrophication status of coastal waters using easy-to-measure parameters, including chromophoric dissolved organic matter (CDOM), fluorescence excitation-emission matrices, CDOM UV-Vis absorbance, and other water-quality parameters (turbidity, chlorophyll a, and dissolved oxygen). First, we decomposed CDOM excitation-emission matrices (EEMs) by PARAFAC to identify three components. Then, we applied PCA to simplify the complexity of the relationships between the water-quality parameters. Finally, we used the PCA score values as independent variables in DFA to develop a eutrophication assessment model. The developed model yielded classification accuracy rates of 97.1%, 80.5%, 90.3%, and 89.1% for good, moderate, and poor water qualities, and for the overall data sets, respectively. Our results suggest that these easy-to-measure parameters could be used to develop a simple approach for rapid in-situ assessment and monitoring of the eutrophication of estuarine and offshore areas.

Assessment and quantification of post-weaning multi-systemic wasting syndrome severity at farm level.

PubMed

Alarcon, Pablo; Velasova, Martina; Werling, Dirk; Stärk, Katharina D C; Chang, Yu-Mei; Nevel, Amanda; Pfeiffer, Dirk U; Wieland, Barbara

2011-01-01

Post-weaning multi-systemic wasting syndrome (PMWS) causes major economic losses for the English pig industry and severity of clinical signs and economic impact vary considerably between affected farms. We present here a novel approach to quantify severity of PMWS based on morbidity and mortality data and presence of porcine circovirus type 2 (PCV2). In 2008-2009, 147 pig farms across England, non-vaccinating for PCV2, were enrolled in a cross-sectional study. Factor analysis was used to generate variables representing biologically meaningful aspects of variation among qualitative and quantitative morbidity variables. Together with other known variables linked to PMWS, the resulting factors were included in a principal component analysis (PCA) to derive an algorithm for PMWS severity. Factor analysis resulted in two factors: Morbidity Factor 1 (MF1) representing mainly weaner and grower morbidity, and Morbidity Factor 2 (MF2) which mainly reflects variation in finisher morbidity. This indicates that farms either had high morbidity mainly in weaners/growers or mainly in finishers. Subsequent PCA resulted in the extraction of one component representing variation in MF1, post-weaning mortality and percentage of PCV2 PCR positive animals. Component scores were normalised to a value range from 0 to 10 and farms classified into: non or slightly affected farms with a score <4, moderately affected farms with scores 4-6.5 and highly affected farms with a score >6.5. The identified farm level PMWS severities will be used to identify risk factors related to these, to assess the efficacy of PCV2 vaccination and investigating the economic impact of potential control measures. Copyright © 2010 Elsevier B.V. All rights reserved.

Tissue factor and Toll-like receptor (TLR)4 in hyperglycaemia-hyperinsulinaemia. Effects in healthy subjects, and type 1 and type 2 diabetes mellitus.

PubMed

Singh, Anamika; Boden, Guenther; Rao, A Koneti

2015-04-01

Diabetes mellitus (DM) patients have an increased incidence of cardiovascular events. Blood tissue factor-procoagulant activity (TF-PCA), the initiating mechanism for blood coagulation, is elevated in DM. We have shown that hyperglycaemia (HG), hyperinsulinaemia (HI) and combined HG+HI (induced using 24-hour infusion clamps) increases TF-PCA in healthy and type 2 DM (T2DM) subjects, but not in type 1 DM (T1DM) subjects. The mechanisms for this are unknown. DM patients have elevated plasma lipopolysaccharide (LPS), a toll-like receptor (TLR) 4 ligand. We postulated that TLR4 plays a role in modulating TF levels. We studied the effect of HG+HI on TLR4 and TF-PCA in vivo during 24-hour HG+HI infusion clamps in healthy subjects, and T1DM and T2DM subjects, and in vitro in blood. In vivo, in healthy subjects, 24-hour HG + HI infusion increased TLR4 six-fold, which correlated with TF-PCA (r= 0.91, p<0.0001). T2DM patients showed smaller increases in both. In T1DM subjects, TLR4 declined (50%, p<0.05) and correlated with TF-PCA (r=0.55; p<0.05). In vitro, HG (200 mg/dl added glucose) and HI (1-100 nM added insulin) increased TF-PCA in healthy subjects (~2-fold, 2-4 hours). Insulin inhibited by ~30% LPS-induced increase in TF-PCA and high glucose reversed it. TLR4 levels paralleled TF-PCA (r=0.71, p<0.0001); HG and HI increased TLR4 and insulin inhibited LPS-induced TLR4 increase. This is first evidence that even in healthy subjects, HG of short duration increases TLR4 and TF-PCA, key players in inflammation and thrombosis. TLR4-TF interplay is strikingly different in non-diabetic, T1DM and T2DM subjects.

Tissue Factor and Toll Like Receptor (TLR)4 in Hyperglycemia-Hyperinsulinemia: Effects in Healthy Subjects, and Type 1 and Type 2 Diabetes Mellitus

PubMed Central

Singh, Anamika; Boden, Guenther; Rao, A. Koneti

2015-01-01

SUMMARY Background Diabetes mellitus (DM) patients have increased cardiovascular events. Blood tissue factor-procoagulant activity (TF-PCA), the initiating mechanism for blood coagulation, is elevated in DM. We have shown that hyperglycemia (HG), hyperinsulinemia (HI) and combined HG+HI (induced using 24 hr infusion clamps) increases TF-PCA in healthy and T2DM subjects, but not in T1DM subjects. The mechanisms for this are unknown. DM patients have elevated plasma lipopolysaccharide (LPS), a toll-like receptor (TLR) 4 ligand. We postulated that TLR4 plays a role in modulating TF levels. Objectives and Methods We studied the effect of HG+HI on TLR4 and TF-PCA in vivo during 24 hr HG+HI infusion clamps in healthy subjects, and T1DM and T2DM subjects, and in vitro in blood. Results In vivo, in healthy subjects, 24 hr HG + HI infusion increased TLR4 6-fold, which correlated with TF-PCA (r= 0.91, p<0.0001). T2DM patients showed smaller increases in both. In T1DM subjects, TLR4 declined (50%, p<0.05) and correlated with TF-PCA (r=0.55; p<0.05). In vitro, HG (200 mg/dl added glucose) and HI (1-100 nM added insulin) increased TF-PCA in healthy subjects (~2-fold, 2-4 hr). Insulin inhibited by ~30% LPS-induced increase in TF-PCA and high glucose reversed it. TLR4 levels paralleled TF-PCA (r=0.71, p<0.0001); HG and HI increased TLR4 and insulin inhibited LPS-induced TLR4 increase. Conclusions This is first evidence that even in healthy subjects, HG of short duration increases TLR4 and TF-PCA, key players in inflammation and thrombosis. TLR4-TF interplay is strikingly different in non-diabetic, T1DM and T2DM subjects. PMID:25653143

Weak acid extractable metals in Bramble Bay, Queensland, Australia: temporal behaviour, enrichment and source apportionment.

PubMed

Brady, James P; Ayoko, Godwin A; Martens, Wayde N; Goonetilleke, Ashantha

2015-02-15

Sediment samples were taken from six sampling sites in Bramble Bay, Queensland, Australia between February and November in 2012. They were analysed for a range of heavy metals including Al, Fe, Mn, Ti, Ce, Th, U, V, Cr, Co, Ni, Cu, Zn, As, Cd, Sb, Te, Hg, Tl and Pb. Fraction analysis, Enrichment Factors and Principal Component Analysis-Absolute Principal Component Scores (PCA-APCS) were carried out in order to assess metal pollution, potential bioavailability and source apportionment. Cr and Ni exceeded the Australian Interim Sediment Quality Guidelines at some sampling sites, while Hg was found to be the most enriched metal. Fraction analysis identified increased weak acid soluble Hg and Cd during the sampling period. Source apportionment via PCA-APCS found four sources of metals pollution, namely, marine sediments, shipping, antifouling coatings and a mixed source. These sources need to be considered in any metal pollution control measure within Bramble Bay. Copyright © 2014 Elsevier Ltd. All rights reserved.

Dynamic viscoelasticity of protease-treated rice batters for gluten-free rice bread making.

PubMed

Honda, Yuji; Inoue, Nanami; Sugimoto, Reina; Matsumoto, Kenji; Koda, Tomonori; Nishioka, Akihiro

2018-03-01

Papain (cysteine protease), subtilisin (Protin SD-AY10, serine protease), and bacillolysin (Protin SD-NY10, metallo protease) increased the specific volume of gluten-free rice breads by 19-63% compared to untreated bread. In contrast, Newlase F (aspartyl protease) did not expand the volume of the rice bread. In a rheological analysis, the viscoelastic properties of the gluten-free rice batters also depended on the protease categories. Principal component analysis (PCA) analysis suggested that the storage and loss moduli (G' and G″, respectively) at 35 °C, and the maximum values of G' and G″, were important factors in the volume expansion. Judging from the PCA of the viscoelastic parameters of the rice batters, papain and Protin SD-AY10 improved the viscoelasticity for gluten-free rice bread making, and Protin SD-NY effectively expanded the gluten-free rice bread. The rheological properties differed between Protin SD-NY and the other protease treatments.

Adaptive online monitoring for ICU patients by combining just-in-time learning and principal component analysis.

PubMed

Li, Xuejian; Wang, Youqing

2016-12-01

Offline general-type models are widely used for patients' monitoring in intensive care units (ICUs), which are developed by using past collected datasets consisting of thousands of patients. However, these models may fail to adapt to the changing states of ICU patients. Thus, to be more robust and effective, the monitoring models should be adaptable to individual patients. A novel combination of just-in-time learning (JITL) and principal component analysis (PCA), referred to learning-type PCA (L-PCA), was proposed for adaptive online monitoring of patients in ICUs. JITL was used to gather the most relevant data samples for adaptive modeling of complex physiological processes. PCA was used to build an online individual-type model and calculate monitoring statistics, and then to judge whether the patient's status is normal or not. The adaptability of L-PCA lies in the usage of individual data and the continuous updating of the training dataset. Twelve subjects were selected from the Physiobank's Multi-parameter Intelligent Monitoring for Intensive Care II (MIMIC II) database, and five vital signs of each subject were chosen. The proposed method was compared with the traditional PCA and fast moving-window PCA (Fast MWPCA). The experimental results demonstrated that the fault detection rates respectively increased by 20 % and 47 % compared with PCA and Fast MWPCA. L-PCA is first introduced into ICU patients monitoring and achieves the best monitoring performance in terms of adaptability to changes in patient status and sensitivity for abnormality detection.

Experimental Researches on the Durability Indicators and the Physiological Comfort of Fabrics using the Principal Component Analysis (PCA) Method

NASA Astrophysics Data System (ADS)

Hristian, L.; Ostafe, M. M.; Manea, L. R.; Apostol, L. L.

2017-06-01

The work pursued the distribution of combed wool fabrics destined to manufacturing of external articles of clothing in terms of the values of durability and physiological comfort indices, using the mathematical model of Principal Component Analysis (PCA). Principal Components Analysis (PCA) applied in this study is a descriptive method of the multivariate analysis/multi-dimensional data, and aims to reduce, under control, the number of variables (columns) of the matrix data as much as possible to two or three. Therefore, based on the information about each group/assortment of fabrics, it is desired that, instead of nine inter-correlated variables, to have only two or three new variables called components. The PCA target is to extract the smallest number of components which recover the most of the total information contained in the initial data.

Biochemical signatures of in vitro radiation response in human lung, breast and prostate tumour cells observed with Raman spectroscopy

NASA Astrophysics Data System (ADS)

Matthews, Q.; Jirasek, A.; Lum, J. J.; Brolo, A. G.

2011-11-01

This work applies noninvasive single-cell Raman spectroscopy (RS) and principal component analysis (PCA) to analyze and correlate radiation-induced biochemical changes in a panel of human tumour cell lines that vary by tissue of origin, p53 status and intrinsic radiosensitivity. Six human tumour cell lines, derived from prostate (DU145, PC3 and LNCaP), breast (MDA-MB-231 and MCF7) and lung (H460), were irradiated in vitro with single fractions (15, 30 or 50 Gy) of 6 MV photons. Remaining live cells were harvested for RS analysis at 0, 24, 48 and 72 h post-irradiation, along with unirradiated controls. Single-cell Raman spectra were acquired from 20 cells per sample utilizing a 785 nm excitation laser. All spectra (200 per cell line) were individually post-processed using established methods and the total data set for each cell line was analyzed with PCA using standard algorithms. One radiation-induced PCA component was detected for each cell line by identification of statistically significant changes in the PCA score distributions for irradiated samples, as compared to unirradiated samples, in the first 24-72 h post-irradiation. These RS response signatures arise from radiation-induced changes in cellular concentrations of aromatic amino acids, conformational protein structures and certain nucleic acid and lipid functional groups. Correlation analysis between the radiation-induced PCA components separates the cell lines into three distinct RS response categories: R1 (H460 and MCF7), R2 (MDA-MB-231 and PC3) and R3 (DU145 and LNCaP). These RS categories partially segregate according to radiosensitivity, as the R1 and R2 cell lines are radioresistant (SF2 > 0.6) and the R3 cell lines are radiosensitive (SF2 < 0.5). The R1 and R2 cell lines further segregate according to p53 gene status, corroborated by cell cycle analysis post-irradiation. Potential radiation-induced biochemical response mechanisms underlying our RS observations are proposed, such as (1) the regulated synthesis and degradation of structured proteins and (2) the expression of anti-apoptosis factors or other survival signals. This study demonstrates the utility of RS for noninvasive radiobiological analysis of tumour cell radiation response, and indicates the potential for future RS studies designed to investigate, monitor or predict radiation response.

Resolution of coi-dominant phytoplankton species in a eutrophiclake using synchrotron-based Fourier transform infraredspectroscopy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dean, A.P.; Martin, Michael C.; Sigee, D.C.

2006-10-09

Synchrotron-based Fourier-transform infrared (FTIR)microspectroscopy was used to distinguish micropopulations of thecodominant algae Microcystis aeruginosa (Cyanophyceae) and Ceratiumhirundinella (Dinophyceae) in mixed phytoplankton samples taken from thewater column of a stratified eutrophic lake (Rostherne Mere, UK). FTIRspectra of the two algae showed a closely similar sequence of 10 bandsover the wave-number range 4000-900 cm-1. These were assigned to a rangeof vibrationally active chemical groups using published band assignmentsand on the basis of correlation and factor analysis. In both algae,intracellular concentrations of macromolecular components (determined asband intensity) varied considerably within the same population,indicating substantial intraspecific heterogeneity. Interspecificdifferences were separately analysed in relation tomore » discrete bands and bymultivariate analysis of the entire spectral region 1750-900 cm-1. Interms of discrete bands, comparison of individual intensities (normalisedto amide 1) demonstrated significant (99 percent probability level)differences in relation to six bands between the two algal species. Keyinterspecific differences were also noted in relation to the positions ofbands 2, 10 (carbohydrate) and 7 (protein) and in the 3-D plots derivedby principal component analysis (PCA) of the sequence of bandintensities. PCA of entire spectral regions showed clear resolutionofspecies in the PCA plot, with indication of separation on the basis ofprotein (region 1700-1500 cm1) and carbohydrate (region 1150-900 cm1)composition in the loading plot. Hierarchical cluster analysis (Wardalgorithm) of entire spectral regions also showed clear discrimination ofthe two species within the resulting dendrogram.« less

STAMP2 increases oxidative stress and is critical for prostate cancer

PubMed Central

Jin, Yang; Wang, Ling; Qu, Su; Sheng, Xia; Kristian, Alexandr; Mælandsmo, Gunhild M; Pällmann, Nora; Yuca, Erkan; Tekedereli, Ibrahim; Gorgulu, Kivanc; Alpay, Neslihan; Sood, Anil; Lopez-Berestein, Gabriel; Fazli, Ladan; Rennie, Paul; Risberg, Bjørn; Wæhre, Håkon; Danielsen, Håvard E; Ozpolat, Bulent; Saatcioglu, Fahri

2015-01-01

The six transmembrane protein of prostate 2 (STAMP2) is an androgen-regulated gene whose mRNA expression is increased in prostate cancer (PCa). Here, we show that STAMP2 protein expression is increased in human PCa compared with benign prostate that is also correlated with tumor grade and treatment response. We also show that STAMP2 significantly increased reactive oxygen species (ROS) in PCa cells through its iron reductase activity which also depleted NADPH levels. Knockdown of STAMP2 expression in PCa cells inhibited proliferation, colony formation, and anchorage-independent growth, and significantly increased apoptosis. Furthermore, STAMP2 effects were, at least in part, mediated by activating transcription factor 4 (ATF4), whose expression is regulated by ROS. Consistent with in vitro findings, silencing STAMP2 significantly inhibited PCa xenograft growth in mice. Finally, therapeutic silencing of STAMP2 by systemically administered nanoliposomal siRNA profoundly inhibited tumor growth in two established preclinical PCa models in mice. These data suggest that STAMP2 is required for PCa progression and thus may serve as a novel therapeutic target. PMID:25680860

Physical fitness in persons with hemiparetic stroke: its structure and longitudinal changes during an inpatient rehabilitation programme.

PubMed

Tsuji, Tetsuya; Liu, Meigen; Hase, Kimitaka; Masakado, Yoshihisa; Takahashi, Hidetoshi; Hara, Yukihiro; Chino, Naoichi

2004-06-01

To test the hypothesis that the structure of fitness in patients with hemiparetic stroke can be categorized into impairment/disability, cardiopulmonary, muscular and metabolic domains, and to study longitudinal changes in their fitness during an inpatient rehabilitation programme. Structure analysis of multiple fitness parameters with principal component analysis (PCA), and a before and after trial. Tertiary rehabilitation centre in Japan. One hundred and seven consecutive inpatients with hemiparetic stroke. A conventional stroke rehabilitation programme consisting of 80 minutes of physical therapy and occupational therapy sessions five days a week, and daily rehabilitation nursing for a median duration of 105.5 days. Principal component scores extracted from measurement of paresis/daily living (the Stroke Impairment Assessment Set (SIAS) and the Functional Independence Measure (FIM)); muscular (grip strength (GS), knee extensor torque, and cross-sectional areas of thigh muscles); metabolic (body mass index (BMI) and fat accumulation on CT); cardiopulmonary (heart rate oxygen coefficient (HR-O2-Coeff) obtained with a graded bridging activity and a 12-minute propulsion distance). PCA categorized the original 15 variables into four factors corresponding to paresis/activities of daily living, muscular, metabolic and cardiopulmonary domains, and explained 78.1% of the total variance at admission and 69.6% at discharge. Except the metabolic domain, PCA scores for the other three domains improved significantly at discharge (paired t-test, p < 0.05). The hypothetical structure of fitness was confirmed, and the PCA scores were useful in following longitudinal changes of fitness during inpatient rehabilitation.

An electrophysiological index of changes in risk decision-making strategies.

PubMed

Zhang, Dandan; Gu, Ruolei; Wu, Tingting; Broster, Lucas S; Luo, Yi; Jiang, Yang; Luo, Yue-jia

2013-07-01

Human decision-making is significantly modulated by previously experienced outcomes. Using event-related potentials (ERPs), we examined whether ERP components evoked by outcome feedbacks could serve as biomarkers to signal the influence of current outcome evaluation on subsequent decision-making. In this study, 18 adult volunteers participated in a simple monetary gambling task, in which they were asked to choose between two options that differed in risk. Their decisions were immediately followed by outcome presentation. Temporospatial principle component analysis (PCA) was applied to the outcome-onset locked ERPs in the 200-1000 ms time window. The PCA factors that approximated classical ERP components (P2, feedback-related negativity, P3a, and P3b) in terms of time course and scalp distribution were tested for their association with subsequent decision-making strategies. Our results revealed that a fronto-central PCA factor approximating the classical P3a was related to changes of decision-making strategies on subsequent trials. The decision to switch between high- and low-risk options resulted in a larger P3a relative to the decision to retain the same choice. According to the results, we suggest that the amplitude of the fronto-central P3a is an electrophysiological index of the influence of current outcome on subsequent risk decision-making. Furthermore, the ERP source analysis indicated that the activations of the frontopolar cortex and sensorimotor cortex were involved in subsequent changes of strategies, which enriches our understanding of the neural mechanisms of adjusting decision-making strategies based on previous experience. Copyright © 2013 Elsevier Ltd. All rights reserved.

Decreased number of mast cells infiltrating into needle biopsy specimens leads to a better prognosis of prostate cancer

PubMed Central

Nonomura, N; Takayama, H; Nishimura, K; Oka, D; Nakai, Y; Shiba, M; Tsujimura, A; Nakayama, M; Aozasa, K; Okuyama, A

2007-01-01

Mast cell infiltration is often observed around human tumours. Inflammatory cells such as macrophages, neutrophils and mast cells infiltrating around tumours are known to contribute to tumour growth; however, the clinical significance of mast cell invasion in prostate cancer (PCa) has not been investigated. Mast cell infiltration was evaluated in 104 patients (age range, 45–88 years; median, 72 years), who underwent needle biopsy of the prostate and were confirmed to have PCa. Needle biopsy specimens of prostate were sliced into 5-μm-thick sections and immunostained for mast cells with monoclonal antibody against mast cell-specific tryptase. Mast cells were counted systematically under a microscope (× 400 magnification), and the relations between mast cell numbers and clinicopathologic findings were evaluated. The mast cell count was evaluated for prognostic value by multivariate analysis. Mast cells were immunostained around the cancer foci. The median number of mast cells in each case was 16. The mast cell count was higher around cancer foci in patients with higher Gleason scores than in those with low Gleason scores. The mast cell number correlated well with clinical stage (P<0.001). Prostate-specific antigen-free survival of patients with higher mast cell counts was better than that in patients with lower mast cell counts (P<0.001). Multivariate analysis revealed that mast cell count was a significant prognostic factor (P<0.005). The number of mast cells infiltrating around cancer foci in prostate biopsy specimens can be a significant prognostic factor of PCa. PMID:17848955

An electrophysiological index of changes in risk decision-making strategies

PubMed Central

Zhang, Dandan; Gu, Ruolei; Wu, Tingting; Broster, Lucas S.; Luo, Yi; Jiang, Yang; Luo, Yue-jia

2014-01-01

Human decision-making is significantly modulated by previously experienced outcomes. Using event-related potentials (ERPs), we examined whether ERP components evoked by outcome feedbacks could serve as biomarkers to signal the influence of current outcome evaluation on subsequent decision-making. In this study, eighteen adult volunteers participated in a simple monetary gambling task, in which they were asked to choose between two options that differed in risk. Their decisions were immediately followed by outcome presentation. Temporospatial principle component analysis (PCA) was applied to the outcome-onset locked ERPs in the -200 – 1000 ms time window. The PCA factors that approximated classical ERP components (P2, feedback-related negativity, P3a, & P3b) in terms of time course and scalp distribution were tested for their association with subsequent decision-making strategies. Our results revealed that a fronto-central PCA factor approximating the classical P3a was related to changes of decision-making strategies on subsequent trials. The decision to switch between high- and low-risk options resulted in a larger P3a relative to the decision to retain the same choice. According to the results, we suggest the amplitude of the fronto-central P3a is an electrophysiological index of the influence of current outcome on subsequent risk decision-making. Furthermore, the ERP source analysis indicated that the activations of the frontopolar cortex and sensorimotor cortex were involved in subsequent changes of strategies, which enriches our understanding of the neural mechanisms of adjusting decision-making strategies based on previous experience. PMID:23643796

The Health Effects of Masculine Self-Esteem Following Treatment for Localized Prostate Cancer Among Gay Men.

PubMed

Allensworth-Davies, Donald; Talcott, James A; Heeren, Timothy; de Vries, Brian; Blank, Thomas O; Clark, Jack A

2015-12-24

To identify factors associated with masculine self-esteem in gay men following treatment for localized prostate cancer (PCa) and to determine the association between masculine self-esteem, PCa-specific factors, and mental health factors in these patients. A national cross-sectional survey of gay PCa survivors was conducted in 2010-2011. To be eligible for the study, men needed to be age 50 or older, reside in the United States, self-identify as gay, able to read, write, and speak English, and to have been treated for PCa at least 1 year ago. One hundred eleven men returned surveys. After simultaneously adjusting for the factors in our model, men aged 50-64 years and men aged 65-74 years reported lower masculine self-esteem scores than men aged 75 years or older. Lower scores were also reported by men who reported recent severe stigma. Men who reported feeling comfortable revealing their sexual orientation to their doctor reported higher masculine self-esteem scores than men who were not. The mental component score from the SF-12 was also positively correlated with masculine self-esteem. PCa providers are in a position to reduce feelings of stigma and promote resiliency by being aware that they might have gay patients, creating a supportive environment where gay patients can discuss specific sexual concerns, and engaging patients in treatment decisions. These efforts could help not only in reducing stigma but also in increasing masculine self-esteem, thus greatly influencing gay patients' recovery, quality of life, and compliance with follow-up care.

Phases of female sexual response cycle among Malaysian women with infertility: a factor analysis study.

PubMed

Seen Heng, Yeoh; Sidi, Hatta; Nik Jaafar, Nik Ruzyanei; Razali, Rosdinom; Ram, Hari

2013-04-01

This cross-sectional study aimed to determine the construct of the phases of the female sexual response cycle (SRC) among women attending an infertility clinic in a Malaysian tertiary center. The sexual response phases were measured with a validated Malay version of the Female Sexual Function Index (FSFI). The correlation structure of the items of the SRC phases (i.e. desire, arousal, orgasm, satisfaction and pain) was determined using principal component analysis (PCA), with varimax rotation method. The number of factors obtained was decided using Kaiser's criteria. A total of 150 married women with a mean age of 32 years participated in this study. Factor loadings using PCA with varimax rotation divided the sexual domains into three components. The first construct comprised sexual arousal, lubrication and pain (suggesting a mechanical component). The second construct were orgasm and sexual satisfaction (suggesting a physical achievement). Sexual desire, suggesting a psychological component, stood on its own as the third. The findings suggest that three constructs could be identified and in favor of the Basson model (a non-linear concept of SRC) for Malaysian women's sexual functioning. Understanding this would help clinicians to strategize the treatment approach of sexual dysfunction in women with infertility. Copyright © 2013 Wiley Publishing Asia Pty Ltd.

Free energy landscape of a biomolecule in dihedral principal component space: sampling convergence and correspondence between structures and minima.

PubMed

Maisuradze, Gia G; Leitner, David M

2007-05-15

Dihedral principal component analysis (dPCA) has recently been developed and shown to display complex features of the free energy landscape of a biomolecule that may be absent in the free energy landscape plotted in principal component space due to mixing of internal and overall rotational motion that can occur in principal component analysis (PCA) [Mu et al., Proteins: Struct Funct Bioinfo 2005;58:45-52]. Another difficulty in the implementation of PCA is sampling convergence, which we address here for both dPCA and PCA using a tetrapeptide as an example. We find that for both methods the sampling convergence can be reached over a similar time. Minima in the free energy landscape in the space of the two largest dihedral principal components often correspond to unique structures, though we also find some distinct minima to correspond to the same structure. 2007 Wiley-Liss, Inc.

Descriptive Characteristics of Surface Water Quality in Hong Kong by a Self-Organising Map

PubMed Central

An, Yan; Zou, Zhihong; Li, Ranran

2016-01-01

In this study, principal component analysis (PCA) and a self-organising map (SOM) were used to analyse a complex dataset obtained from the river water monitoring stations in the Tolo Harbor and Channel Water Control Zone (Hong Kong), covering the period of 2009–2011. PCA was initially applied to identify the principal components (PCs) among the nonlinear and complex surface water quality parameters. SOM followed PCA, and was implemented to analyze the complex relationships and behaviors of the parameters. The results reveal that PCA reduced the multidimensional parameters to four significant PCs which are combinations of the original ones. The positive and inverse relationships of the parameters were shown explicitly by pattern analysis in the component planes. It was found that PCA and SOM are efficient tools to capture and analyze the behavior of multivariable, complex, and nonlinear related surface water quality data. PMID:26761018

Descriptive Characteristics of Surface Water Quality in Hong Kong by a Self-Organising Map.

PubMed

An, Yan; Zou, Zhihong; Li, Ranran

2016-01-08

In this study, principal component analysis (PCA) and a self-organising map (SOM) were used to analyse a complex dataset obtained from the river water monitoring stations in the Tolo Harbor and Channel Water Control Zone (Hong Kong), covering the period of 2009-2011. PCA was initially applied to identify the principal components (PCs) among the nonlinear and complex surface water quality parameters. SOM followed PCA, and was implemented to analyze the complex relationships and behaviors of the parameters. The results reveal that PCA reduced the multidimensional parameters to four significant PCs which are combinations of the original ones. The positive and inverse relationships of the parameters were shown explicitly by pattern analysis in the component planes. It was found that PCA and SOM are efficient tools to capture and analyze the behavior of multivariable, complex, and nonlinear related surface water quality data.

Analysis of Zinc-Exporters Expression in Prostate Cancer.

PubMed

Singh, Chandra K; Malas, Kareem M; Tydrick, Caitlin; Siddiqui, Imtiaz A; Iczkowski, Kenneth A; Ahmad, Nihal

2016-11-11

Maintaining optimal intracellular zinc (Zn) concentration is crucial for critical cellular functions. Depleted Zn has been associated with prostate cancer (PCa) progression. Solute carrier family 30 (SLC30A) proteins maintain cytoplasmic Zn balance by exporting Zn out to the extracellular space or by sequestering cytoplasmic Zn into intracellular compartments. In this study, we determined the involvement of Zn-exporters, SLC30A 1-10 in PCa, in the context of racial health disparity in human PCa samples obtained from European-American (EA) and African-American (AA) populations. We also analyzed the levels of Zn-exporters in a panel of PCa cells derived from EA and AA populations. We further explored the expression profile of Zn-exporters in PCa using Oncomine database. Zn-exporters were found to be differentially expressed at the mRNA level, with a significant upregulation of SLC30A1, SLC30A9 and SLC30A10, and downregulation of SLC30A5 and SLC30A6 in PCa, compared to benign prostate. Moreover, Ingenuity Pathway analysis revealed several interactions of Zn-exporters with certain tumor suppressor and promoter proteins known to be modulated in PCa. Our study provides an insight regarding Zn-exporters in PCa, which may open new avenues for future studies aimed at enhancing the levels of Zn by modulating Zn-transporters via pharmacological means.

Analysis of Zinc-Exporters Expression in Prostate Cancer

PubMed Central

Singh, Chandra K.; Malas, Kareem M.; Tydrick, Caitlin; Siddiqui, Imtiaz A.; Iczkowski, Kenneth A.; Ahmad, Nihal

2016-01-01

Maintaining optimal intracellular zinc (Zn) concentration is crucial for critical cellular functions. Depleted Zn has been associated with prostate cancer (PCa) progression. Solute carrier family 30 (SLC30A) proteins maintain cytoplasmic Zn balance by exporting Zn out to the extracellular space or by sequestering cytoplasmic Zn into intracellular compartments. In this study, we determined the involvement of Zn-exporters, SLC30A 1–10 in PCa, in the context of racial health disparity in human PCa samples obtained from European-American (EA) and African-American (AA) populations. We also analyzed the levels of Zn-exporters in a panel of PCa cells derived from EA and AA populations. We further explored the expression profile of Zn-exporters in PCa using Oncomine database. Zn-exporters were found to be differentially expressed at the mRNA level, with a significant upregulation of SLC30A1, SLC30A9 and SLC30A10, and downregulation of SLC30A5 and SLC30A6 in PCa, compared to benign prostate. Moreover, Ingenuity Pathway analysis revealed several interactions of Zn-exporters with certain tumor suppressor and promoter proteins known to be modulated in PCa. Our study provides an insight regarding Zn-exporters in PCa, which may open new avenues for future studies aimed at enhancing the levels of Zn by modulating Zn-transporters via pharmacological means. PMID:27833104

Detecting phase separation of freeze-dried binary amorphous systems using pair-wise distribution function and multivariate data analysis.

PubMed

Chieng, Norman; Trnka, Hjalte; Boetker, Johan; Pikal, Michael; Rantanen, Jukka; Grohganz, Holger

2013-09-15

The purpose of this study is to investigate the use of multivariate data analysis for powder X-ray diffraction-pair-wise distribution function (PXRD-PDF) data to detect phase separation in freeze-dried binary amorphous systems. Polymer-polymer and polymer-sugar binary systems at various ratios were freeze-dried. All samples were analyzed by PXRD, transformed to PDF and analyzed by principal component analysis (PCA). These results were validated by differential scanning calorimetry (DSC) through characterization of glass transition of the maximally freeze-concentrate solute (Tg'). Analysis of PXRD-PDF data using PCA provides a more clear 'miscible' or 'phase separated' interpretation through the distribution pattern of samples on a score plot presentation compared to residual plot method. In a phase separated system, samples were found to be evenly distributed around the theoretical PDF profile. For systems that were miscible, a clear deviation of samples away from the theoretical PDF profile was observed. Moreover, PCA analysis allows simultaneous analysis of replicate samples. Comparatively, the phase behavior analysis from PXRD-PDF-PCA method was in agreement with the DSC results. Overall, the combined PXRD-PDF-PCA approach improves the clarity of the PXRD-PDF results and can be used as an alternative explorative data analytical tool in detecting phase separation in freeze-dried binary amorphous systems. Copyright © 2013 Elsevier B.V. All rights reserved.

24 CFR 401.451 - PAE Physical Condition Analysis (PCA).

Code of Federal Regulations, 2010 CFR

2010-04-01

... PROGRAM (MARK-TO-MARKET) Restructuring Plan § 401.451 PAE Physical Condition Analysis (PCA). (a) Review and certification of owner evaluation. (1) The PAE must independently evaluate the physical condition... 24 Housing and Urban Development 2 2010-04-01 2010-04-01 false PAE Physical Condition Analysis...

24 CFR 401.451 - PAE Physical Condition Analysis (PCA).

Code of Federal Regulations, 2013 CFR

2013-04-01

... 24 Housing and Urban Development 2 2013-04-01 2013-04-01 false PAE Physical Condition Analysis... PROGRAM (MARK-TO-MARKET) Restructuring Plan § 401.451 PAE Physical Condition Analysis (PCA). (a) Review and certification of owner evaluation. (1) The PAE must independently evaluate the physical condition...

24 CFR 401.451 - PAE Physical Condition Analysis (PCA).

Code of Federal Regulations, 2011 CFR

2011-04-01

... 24 Housing and Urban Development 2 2011-04-01 2011-04-01 false PAE Physical Condition Analysis... PROGRAM (MARK-TO-MARKET) Restructuring Plan § 401.451 PAE Physical Condition Analysis (PCA). (a) Review and certification of owner evaluation. (1) The PAE must independently evaluate the physical condition...

24 CFR 401.451 - PAE Physical Condition Analysis (PCA).

Code of Federal Regulations, 2012 CFR

2012-04-01

... 24 Housing and Urban Development 2 2012-04-01 2012-04-01 false PAE Physical Condition Analysis... PROGRAM (MARK-TO-MARKET) Restructuring Plan § 401.451 PAE Physical Condition Analysis (PCA). (a) Review and certification of owner evaluation. (1) The PAE must independently evaluate the physical condition...

24 CFR 401.451 - PAE Physical Condition Analysis (PCA).

Code of Federal Regulations, 2014 CFR

2014-04-01

... 24 Housing and Urban Development 2 2014-04-01 2014-04-01 false PAE Physical Condition Analysis... PROGRAM (MARK-TO-MARKET) Restructuring Plan § 401.451 PAE Physical Condition Analysis (PCA). (a) Review and certification of owner evaluation. (1) The PAE must independently evaluate the physical condition...

Characterizing the molecular features of ERG-positive tumors in primary and castration resistant prostate cancer

PubMed Central

Roudier, Martine P; Winters, Brian R; Coleman, Ilsa; Lam, Hung-Ming; Zhang, Xiaotun; Coleman, Roger; Chéry, Lisly; True, Lawrence D.; Higano, Celestia S.; Montgomery, Bruce; Lange, Paul H.; Snyder, Linda A.; Srivistava, Shiv; Corey, Eva; Vessella, Robert L.; Nelson, Peter S.; Üren, Aykut; Morrissey, Colm

2017-01-01

Background The TMPRSS2-ERG gene fusion is detected in approximately half of primary prostate cancers (PCa) yet the prognostic significance remains unclear. We hypothesized that ERG promotes the expression of common genes in primary PCa and metastatic castration-resistant PCa (CRPC), with the objective of identifying ERG-associated pathways, which may promote the transition from primary PCa to CRPC. Methods We constructed tissue microarrays (TMA) from 127 radical prostatectomy specimens, 20 LuCaP patient-derived xenografts (PDX), and 152 CRPC metastases obtained immediately at time of death. Nuclear ERG was assessed by immunohistochemistry (IHC). To characterize the molecular features of ERG-expressing PCa, a subset of IHC confirmed ERG+ or ERG-specimens including 11 radical prostatectomies, 20 LuCaP PDXs, and 45 CRPC metastases underwent gene expression analysis. Genes were ranked based on expression in primary PCa and CRPC. Common genes of interest were targeted for IHC analysis and expression compared with biochemical recurrence (BCR) status. Results IHC revealed that 43% of primary PCa, 35% of the LuCaP PDXs, and 18% of the CRPC metastases were ERG+ (12 of 48 patients [25%] had at least 1 ERG+ metastasis). Based on gene expression data and previous literature, two proteins involved in calcium signaling (NCALD, CACNA1D), a protein involved in inflammation (HLA-DMB), CD3 positive immune cells, and a novel ERG-associated protein, DCLK1 were evaluated in primary PCa and CRPC metastases. In ERG+ primary PCa, a weak association was seen with NCALD and CACNA1D protein expression. HLA-DMB expression and the presence of CD3 positive immune cells were decreased in CRPC metastases compared to primary PCa. DCLK1 was upregulated at the protein level in unpaired ERG+ primary PCa and CRPC metastases (p=0.0013 and p<0.0001, respectively). In primary PCa, ERG status or expression of targeted proteins was not associated with BCR-free survival. However for primary PCa, ERG+DCLK1+ patients exhibited shorter time to BCR (p=0.06) compared with ERG+DCLK1- patients. Conclusions This study examined ERG expression in primary PCa and CRPC. We have identified altered levels of inflammatory mediators associated with ERG expression. We determined expression of DCLK1 correlates with ERG expression and may play a role in primary PCa progression to metastatic CPRC. PMID:26990456

Cluster and principal component analysis based on SSR markers of Amomum tsao-ko in Jinping County of Yunnan Province

NASA Astrophysics Data System (ADS)

Ma, Mengli; Lei, En; Meng, Hengling; Wang, Tiantao; Xie, Linyan; Shen, Dong; Xianwang, Zhou; Lu, Bingyue

2017-08-01

Amomum tsao-ko is a commercial plant that used for various purposes in medicinal and food industries. For the present investigation, 44 germplasm samples were collected from Jinping County of Yunnan Province. Clusters analysis and 2-dimensional principal component analysis (PCA) was used to represent the genetic relations among Amomum tsao-ko by using simple sequence repeat (SSR) markers. Clustering analysis clearly distinguished the samples groups. Two major clusters were formed; first (Cluster I) consisted of 34 individuals, the second (Cluster II) consisted of 10 individuals, Cluster I as the main group contained multiple sub-clusters. PCA also showed 2 groups: PCA Group 1 included 29 individuals, PCA Group 2 included 12 individuals, consistent with the results of cluster analysis. The purpose of the present investigation was to provide information on genetic relationship of Amomum tsao-ko germplasm resources in main producing areas, also provide a theoretical basis for the protection and utilization of Amomum tsao-ko resources.

A new statistic for identifying batch effects in high-throughput genomic data that uses guided principal component analysis.

PubMed

Reese, Sarah E; Archer, Kellie J; Therneau, Terry M; Atkinson, Elizabeth J; Vachon, Celine M; de Andrade, Mariza; Kocher, Jean-Pierre A; Eckel-Passow, Jeanette E

2013-11-15

Batch effects are due to probe-specific systematic variation between groups of samples (batches) resulting from experimental features that are not of biological interest. Principal component analysis (PCA) is commonly used as a visual tool to determine whether batch effects exist after applying a global normalization method. However, PCA yields linear combinations of the variables that contribute maximum variance and thus will not necessarily detect batch effects if they are not the largest source of variability in the data. We present an extension of PCA to quantify the existence of batch effects, called guided PCA (gPCA). We describe a test statistic that uses gPCA to test whether a batch effect exists. We apply our proposed test statistic derived using gPCA to simulated data and to two copy number variation case studies: the first study consisted of 614 samples from a breast cancer family study using Illumina Human 660 bead-chip arrays, whereas the second case study consisted of 703 samples from a family blood pressure study that used Affymetrix SNP Array 6.0. We demonstrate that our statistic has good statistical properties and is able to identify significant batch effects in two copy number variation case studies. We developed a new statistic that uses gPCA to identify whether batch effects exist in high-throughput genomic data. Although our examples pertain to copy number data, gPCA is general and can be used on other data types as well. The gPCA R package (Available via CRAN) provides functionality and data to perform the methods in this article. reesese@vcu.edu

Application of principal component analysis for improvement of X-ray fluorescence images obtained by polycapillary-based micro-XRF technique

NASA Astrophysics Data System (ADS)

Aida, S.; Matsuno, T.; Hasegawa, T.; Tsuji, K.

2017-07-01

Micro X-ray fluorescence (micro-XRF) analysis is repeated as a means of producing elemental maps. In some cases, however, the XRF images of trace elements that are obtained are not clear due to high background intensity. To solve this problem, we applied principal component analysis (PCA) to XRF spectra. We focused on improving the quality of XRF images by applying PCA. XRF images of the dried residue of standard solution on the glass substrate were taken. The XRF intensities for the dried residue were analyzed before and after PCA. Standard deviations of XRF intensities in the PCA-filtered images were improved, leading to clear contrast of the images. This improvement of the XRF images was effective in cases where the XRF intensity was weak.

DNA-PKcs Expression Is a Predictor of Biochemical Recurrence After Permanent Iodine 125 Interstitial Brachytherapy for Prostate Cancer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Molina, Sarah; Department of Radiation Oncology, CHU/Université de Poitiers, Poitiers; Guerif, Stéphane

Purpose: Predictive factors for biochemical recurrence (BCR) in localized prostate cancer (PCa) after brachytherapy are insufficient to date. Cellular radiosensitivity depends on DNA double-strand breaks, mainly repaired by the nonhomologous end-joining (NHEJ) system. We analyzed whether the expression of NHEJ proteins can predict BCR in patients treated by brachytherapy for localized PCa. Methods and Materials: From 983 PCa cases treated by brachytherapy between March 2000 and March 2012, 167 patients with available biopsy material suitable for in situ analysis were included in the study. The median follow-up time was 47 months. Twenty-nine patients experienced BCR. All slides were reviewed to reassessmore » the Gleason score. Expression of the key NHEJ proteins DNA-PKcs, Ku70, and Ku80, and the proliferation marker Ki67, was studied by immunohistochemistry performed on tissue microarrays. Results: The Gleason scores after review (P=.06) tended to be associated with BCR when compared with the score initially reported (P=.74). Both the clinical stage (P=.02) and the pretreatment prostate-specific antigen level (P=.01) were associated with biochemical failure. Whereas the expression of Ku80 and Ki67 were not predictive of relapse, positive DNA-PKcs nuclear staining (P=.003) and higher Ku70 expression (P=.05) were associated with BCR. On multivariate analysis, among pretreatment variables, only DNA-PKcs (P=.03) and clinical stage (P=.02) remained predictive of recurrence. None of the patients without palpable PCa and negative DNA-PKcs expression experienced biochemical failure, compared with 32% of men with palpable and positive DNA-PKcs staining that recurred. Conclusions: Our results suggest that DNA-PKcs could be a predictive marker of BCR after brachytherapy, and this might be a useful tool for optimizing the choice of treatment in low-risk PCa patients.« less

Contact- and distance-based principal component analysis of protein dynamics.

PubMed

Ernst, Matthias; Sittel, Florian; Stock, Gerhard

2015-12-28

To interpret molecular dynamics simulations of complex systems, systematic dimensionality reduction methods such as principal component analysis (PCA) represent a well-established and popular approach. Apart from Cartesian coordinates, internal coordinates, e.g., backbone dihedral angles or various kinds of distances, may be used as input data in a PCA. Adopting two well-known model problems, folding of villin headpiece and the functional dynamics of BPTI, a systematic study of PCA using distance-based measures is presented which employs distances between Cα-atoms as well as distances between inter-residue contacts including side chains. While this approach seems prohibitive for larger systems due to the quadratic scaling of the number of distances with the size of the molecule, it is shown that it is sufficient (and sometimes even better) to include only relatively few selected distances in the analysis. The quality of the PCA is assessed by considering the resolution of the resulting free energy landscape (to identify metastable conformational states and barriers) and the decay behavior of the corresponding autocorrelation functions (to test the time scale separation of the PCA). By comparing results obtained with distance-based, dihedral angle, and Cartesian coordinates, the study shows that the choice of input variables may drastically influence the outcome of a PCA.

Contact- and distance-based principal component analysis of protein dynamics

NASA Astrophysics Data System (ADS)

Ernst, Matthias; Sittel, Florian; Stock, Gerhard

2015-12-01

To interpret molecular dynamics simulations of complex systems, systematic dimensionality reduction methods such as principal component analysis (PCA) represent a well-established and popular approach. Apart from Cartesian coordinates, internal coordinates, e.g., backbone dihedral angles or various kinds of distances, may be used as input data in a PCA. Adopting two well-known model problems, folding of villin headpiece and the functional dynamics of BPTI, a systematic study of PCA using distance-based measures is presented which employs distances between Cα-atoms as well as distances between inter-residue contacts including side chains. While this approach seems prohibitive for larger systems due to the quadratic scaling of the number of distances with the size of the molecule, it is shown that it is sufficient (and sometimes even better) to include only relatively few selected distances in the analysis. The quality of the PCA is assessed by considering the resolution of the resulting free energy landscape (to identify metastable conformational states and barriers) and the decay behavior of the corresponding autocorrelation functions (to test the time scale separation of the PCA). By comparing results obtained with distance-based, dihedral angle, and Cartesian coordinates, the study shows that the choice of input variables may drastically influence the outcome of a PCA.

Urinary microRNAs for prostate cancer diagnosis, prognosis, and treatment response: are we there yet?

PubMed

Balacescu, Ovidiu; Petrut, Bogdan; Tudoran, Oana; Feflea, Dragos; Balacescu, Loredana; Anghel, Andrei; Sirbu, Ioan O; Seclaman, Edward; Marian, Catalin

2017-11-01

Prostate cancer (PCa) remains one of the leading causes of cancer-related deaths in men. Despite the tremendous progress in research over the years, a suitable minimally invasive PCa biomarker is yet to be discovered. The recent advances regarding the roles of microRNAs as biomarkers has allowed for their study in PCa as well, especially as blood-based markers. However, there are several studies that used urine as biological sample to evaluate microRNAs as biomarkers for PCa diagnosis, prognosis, and treatment response, which were reviewed herein. A high degree of inconsistency among reports has been observed, which could be due to several analytical aspects, starting with different urinary fractions used for analysis and continuing with the employment of various analytical platforms and methods of statistical analysis. However, a few microRNAs were found to be dysregulated in the urine of PCa patients, which alone or together with serum prostate-specific antigen seem to improve diagnostic power even in the gray zone of PCa. These results warrant further confirmation by larger prospective studies, preferably using a standardized protocol for analysis. WIREs RNA 2017, 8:e1438. doi: 10.1002/wrna.1438 For further resources related to this article, please visit the WIREs website. © 2017 Wiley Periodicals, Inc.

Prostate Cancer Patients-Negative Biopsy Controls Discrimination by Untargeted Metabolomics Analysis of Urine by LC-QTOF: Upstream Information on Other Omics

NASA Astrophysics Data System (ADS)

Fernández-Peralbo, M. A.; Gómez-Gómez, E.; Calderón-Santiago, M.; Carrasco-Valiente, J.; Ruiz-García, J.; Requena-Tapia, M. J.; Luque de Castro, M. D.; Priego-Capote, F.

2016-12-01

The existing clinical biomarkers for prostate cancer (PCa) diagnosis are far from ideal (e.g., the prostate specific antigen (PSA) serum level suffers from lack of specificity, providing frequent false positives leading to over-diagnosis). A key step in the search for minimum invasive tests to complement or replace PSA should be supported on the changes experienced by the biochemical pathways in PCa patients as compared to negative biopsy control individuals. In this research a comprehensive global analysis by LC-QTOF was applied to urine from 62 patients with a clinically significant PCa and 42 healthy individuals, both groups confirmed by biopsy. An unpaired t-test (p-value < 0.05) provided 28 significant metabolites tentatively identified in urine, used to develop a partial least squares discriminant analysis (PLS-DA) model characterized by 88.4 and 92.9% of sensitivity and specificity, respectively. Among the 28 significant metabolites 27 were present at lower concentrations in PCa patients than in control individuals, while only one reported higher concentrations in PCa patients. The connection among the biochemical pathways in which they are involved (DNA methylation, epigenetic marks on histones and RNA cap methylation) could explain the concentration changes with PCa and supports, once again, the role of metabolomics in upstream processes.

Substantial Family History of Prostate Cancer in Black Men Recruited for Prostate Cancer Screening

PubMed Central

Mastalski, Kathleen; Coups, Elliot J.; Ruth, Karen; Raysor, Susan; Giri, Veda N.

2008-01-01

Background Black men are at increased risk for prostate cancer (PCA), particularly with a family history (FH) of the disease. Previous reports have raised concern for suboptimal screening of Black men with a FH of PCA. We report on the extent of FH of PCA from a prospective, longitudinal PCA screening program for high-risk men. Methods Black men ages 35-69 are eligible for PCA screening through the Prostate Cancer Risk Assessment Program (PRAP) regardless of FH. Rates of self-reported FH of PCA, breast, and colon cancer at baseline were compared with an age-matched sample of Black men from the 2005 National Health Interview Survey (NHIS) using standard statistical methods. Results As of January 2007, 332 Black men with pedigree information were enrolled in PRAP and FH of PCA was compared to 838 Black men from the 2005 NHIS. Black men in PRAP reported significantly more first-degree relatives with PCA compared to Black men in the 2005 NHIS (34.3%, 95% CI 29.2-39.7 vs. 5.7%, 95% CI 3.9-7.4). Black men in PRAP also had more FH of breast cancer compared to the 2005 NHIS (11.5%, 95% CI 8.2-15.4 vs 6.3%, 95% CI 4.6-8.0). Conclusions FH of PCA appears to be a motivating factor for Black men seeking PCA screening. Targeted recruitment and education among Black families should improve PCA screening rates. Efforts to recruit Black men without a FH of PCA are also needed. Condensed Abstract Black men seeking prostate cancer screening have a substantial burden of family history of prostate cancer. Targeted education and enhancing discussion in Black families should increase prostate cancer screening and adherence. PMID:18816608

Association between baseline serum glucose, triglycerides and total cholesterol, and prostate cancer risk categories.

PubMed

Arthur, Rhonda; Møller, Henrik; Garmo, Hans; Holmberg, Lars; Stattin, Pår; Malmstrom, Håkan; Lambe, Mats; Hammar, Niklas; Walldius, Göran; Robinson, David; Jungner, Ingmar; Hemelrijck, Mieke Van

2016-06-01

Lifestyle-related risk factors such as hyperglycemia and dyslipidemia have been associated with several cancers. However, studies exploring their link with prostate cancer (PCa) clinicopathological characteristics are sparse and inconclusive. Here, we investigated the associations between serum metabolic markers and PCa clinicopathological characteristics. The study comprised 14,294 men from the Swedish Apolipoprotein MOrtality RISk (AMORIS) cohort who were diagnosed with PCa between 1996 and 2011. Univariate and multivariable logistic regression were used to investigate the relation between glucose, triglycerides and total cholesterol and PCa risk categories, PSA, Gleason score, and T-stage. Mean age at time of PCa diagnosis was 69 years. Men with glucose levels >6.9 mmol/L tend to have PSA<4 μg/L, while those with glucose levels of 5.6-6.9 mmol/L had a greater odds of PSA>20 μg/L compared to PSA 4.0-9.9 μg/L. Hypertriglyceridemia was also positively associated with PSA>20 μg/L. Hyperglycemic men had a greater odds of intermediate- and high-grade PCa and advanced stage or metastatic PCa. Similarly, hypertriglyceridemia was positively associated with high-grade PCa. There was also a trend toward an increased odds of intermediate risk localized PCa and advanced stage PCa among men with hypertriglyceridemia. Total cholesterol did not have any statistically significant association with any of the outcomes studied. Our findings suggest that high serum levels of glucose and triglycerides may influence PCa aggressiveness and severity. Further investigation on the role of markers of glucose and lipid metabolism in influencing PCa aggressiveness and severity is needed as this may help define important targets for intervention. © 2016 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.

Inflammation: an important parameter in the search of prostate cancer biomarkers

PubMed Central

2014-01-01

Background A more specific and early diagnostics for prostate cancer (PCa) is highly desirable. In this study, being inflammation the focus of our effort, serum protein profiles were analyzed in order to investigate if this parameter could interfere with the search of discriminating proteins between PCa and benign prostatic hyperplasia (BPH). Methods Patients with clinical suspect of PCa and candidates for trans-rectal ultrasound guided prostate biopsy (TRUS) were enrolled. Histological specimens were examined in order to grade and classify the tumor, identify BPH and detect inflammation. Surface Enhanced Laser Desorption/Ionization-Time of Flight-Mass Spectrometry (SELDI-ToF-MS) and two-dimensional gel electrophoresis (2-DE) coupled with Liquid Chromatography-MS/MS (LC-MS/MS) were used to analyze immuno-depleted serum samples from patients with PCa and BPH. Results The comparison between PCa (with and without inflammation) and BPH (with and without inflammation) serum samples by SELDI-ToF-MS analysis did not show differences in protein expression, while changes were only observed when the concomitant presence of inflammation was taken into consideration. In fact, when samples with histological sign of inflammation were excluded, 20 significantly different protein peaks were detected. Subsequent comparisons (PCa with inflammation vs PCa without inflammation, and BPH with inflammation vs BPH without inflammation) showed that 16 proteins appeared to be modified in the presence of inflammation, while 4 protein peaks were not modified. With 2-DE analysis, comparing PCa without inflammation vs PCa with inflammation, and BPH without inflammation vs the same condition in the presence of inflammation, were identified 29 and 25 differentially expressed protein spots, respectively. Excluding samples with inflammation the comparison between PCa vs BPH showed 9 unique PCa proteins, 4 of which overlapped with those previously identified in the presence of inflammation, while other 2 were new proteins, not identified in our previous comparisons. Conclusions The present study indicates that inflammation might be a confounding parameter during the proteomic research of candidate biomarkers of PCa. These results indicate that some possible biomarker-candidate proteins are strongly influenced by the presence of inflammation, hence only a well-selected protein pattern should be considered for potential marker of PCa. PMID:24944525

Can Prostate Imaging Reporting and Data System Version 2 reduce unnecessary prostate biopsies in men with PSA levels of 4-10 ng/ml?

PubMed

Xu, Ning; Wu, Yu-Peng; Chen, Dong-Ning; Ke, Zhi-Bin; Cai, Hai; Wei, Yong; Zheng, Qing-Shui; Huang, Jin-Bei; Li, Xiao-Dong; Xue, Xue-Yi

2018-05-01

To explore the value of Prostate Imaging Reporting and Data System Version 2 (PI-RADS v2) for predicting prostate biopsy results in patients with prostate specific antigen (PSA) levels of 4-10 ng/ml. We retrospectively reviewed multi-parameter magnetic resonance images from 528 patients with PSA levels of 4-10 ng/ml who underwent transrectal ultrasound-guided prostate biopsies between May 2015 and May 2017. Among them, 137 were diagnosed with prostate cancer (PCa), and we further subdivided them according to pathological results into the significant PCa (S-PCa) and insignificant significant PCa (Ins-PCa) groups (121 cases were defined by surgical pathological specimen and 16 by biopsy). Age, PSA, percent free PSA, PSA density (PSAD), prostate volume (PV), and PI-RADS score were collected. Logistic regression analysis was performed to determine predictors of pathological results. Receiver operating characteristic curves were constructed to analyze the diagnostic value of PI-RADS v2 in PCa. Multivariate analysis indicated that age, PV, percent free PSA, and PI-RADS score were independent predictors of biopsy findings, while only PI-RADS score was an independent predictor of S-PCa (P < 0.05). The areas under the receiver operating characteristic curve for diagnosing PCa with respect to age, PV, percent free PSA, and PI-RADS score were 0.570, 0.430, 0.589 and 0.836, respectively. The area under the curve for diagnosing S-PCa with respect to PI-RADS score was 0.732. A PI-RADS score of 3 was the best cutoff for predicting PCa, and 4 was the best cutoff for predicting S-PCa. Thus, 92.8% of patients with PI-RADS scores of 1-2 would have avoided biopsy, but at the cost of missing 2.2% of the potential PCa cases. Similarly, 83.82% of patients with a PI-RADS score ≤ 3 would have avoided biopsy, but at the cost of missing 3.3% of the potential S-PCa cases. PI-RADS v2 could be used to reduce unnecessary prostate biopsies in patients with PSA levels of 4-10 ng/ml.

In Vitro Assessment of Nanoparticle Effects on Blood Coagulation.

PubMed

Potter, Timothy M; Rodriguez, Jamie C; Neun, Barry W; Ilinskaya, Anna N; Cedrone, Edward; Dobrovolskaia, Marina A

2018-01-01

Blood clotting is a complex process which involves both cellular and biochemical components. The key cellular players in the blood clotting process are thrombocytes or platelets. Other cells, including leukocytes and endothelial cells, contribute to clotting by expressing the so-called pro-coagulant activity (PCA) complex on their surface. The biochemical component of blood clotting is represented by the plasma coagulation cascade, which includes plasma proteins also known as coagulation factors. The coordinated interaction between platelets, leukocytes, endothelial cells, and plasma coagulation factors is necessary for maintaining hemostasis and for preventing excessive bleeding. Undesirable activation of all or some of these components may lead to pathological blood coagulation and life-threatening conditions such as consumptive coagulopathy or disseminated intravascular coagulation (DIC). In contrast, unintended inhibition of the coagulation pathways may lead to hemorrhage. Thrombogenicity is the property of a test material to induce blood coagulation by affecting one or more elements of the clotting process. Anticoagulant activity refers to the property of a test material to inhibit coagulation. The tendency to cause platelet aggregation, perturb plasma coagulation, and induce leukocyte PCA can serve as an in vitro measure of a nanomaterial's likelihood to be pro- or anticoagulant in vivo. This chapter describes three procedures for in vitro analyses of platelet aggregation, plasma coagulation time, and activation of leukocyte PCA. Platelet aggregation and plasma coagulation procedures have been described earlier. The revision here includes updated details about nanoparticle sample preparation, selection of nanoparticle concentration for the in vitro study, and updated details about assay controls. The chapter is expanded to describe a method for the leukocyte PCA analysis and case studies demonstrating the performance of these in vitro assays.

Network Intrusion Detection Based on a General Regression Neural Network Optimized by an Improved Artificial Immune Algorithm

PubMed Central

Wu, Jianfa; Peng, Dahao; Li, Zhuping; Zhao, Li; Ling, Huanzhang

2015-01-01

To effectively and accurately detect and classify network intrusion data, this paper introduces a general regression neural network (GRNN) based on the artificial immune algorithm with elitist strategies (AIAE). The elitist archive and elitist crossover were combined with the artificial immune algorithm (AIA) to produce the AIAE-GRNN algorithm, with the aim of improving its adaptivity and accuracy. In this paper, the mean square errors (MSEs) were considered the affinity function. The AIAE was used to optimize the smooth factors of the GRNN; then, the optimal smooth factor was solved and substituted into the trained GRNN. Thus, the intrusive data were classified. The paper selected a GRNN that was separately optimized using a genetic algorithm (GA), particle swarm optimization (PSO), and fuzzy C-mean clustering (FCM) to enable a comparison of these approaches. As shown in the results, the AIAE-GRNN achieves a higher classification accuracy than PSO-GRNN, but the running time of AIAE-GRNN is long, which was proved first. FCM and GA-GRNN were eliminated because of their deficiencies in terms of accuracy and convergence. To improve the running speed, the paper adopted principal component analysis (PCA) to reduce the dimensions of the intrusive data. With the reduction in dimensionality, the PCA-AIAE-GRNN decreases in accuracy less and has better convergence than the PCA-PSO-GRNN, and the running speed of the PCA-AIAE-GRNN was relatively improved. The experimental results show that the AIAE-GRNN has a higher robustness and accuracy than the other algorithms considered and can thus be used to classify the intrusive data. PMID:25807466

The histogram analysis of diffusion-weighted intravoxel incoherent motion (IVIM) imaging for differentiating the gleason grade of prostate cancer.

PubMed

Zhang, Yu-Dong; Wang, Qing; Wu, Chen-Jiang; Wang, Xiao-Ning; Zhang, Jing; Liu, Hui; Liu, Xi-Sheng; Shi, Hai-Bin

2015-04-01

To evaluate histogram analysis of intravoxel incoherent motion (IVIM) for discriminating the Gleason grade of prostate cancer (PCa). A total of 48 patients pathologically confirmed as having clinically significant PCa (size > 0.5 cm) underwent preoperative DW-MRI (b of 0-900 s/mm(2)). Data was post-processed by monoexponential and IVIM model for quantitation of apparent diffusion coefficients (ADCs), perfusion fraction f, diffusivity D and pseudo-diffusivity D*. Histogram analysis was performed by outlining entire-tumour regions of interest (ROIs) from histological-radiological correlation. The ability of imaging indices to differentiate low-grade (LG, Gleason score (GS) ≤6) from intermediate/high-grade (HG, GS > 6) PCa was analysed by ROC regression. Eleven patients had LG tumours (18 foci) and 37 patients had HG tumours (42 foci) on pathology examination. HG tumours had significantly lower ADCs and D in terms of mean, median, 10th and 75th percentiles, combined with higher histogram kurtosis and skewness for ADCs, D and f, than LG PCa (p < 0.05). Histogram D showed relatively higher correlations (ñ = 0.641-0.668 vs. ADCs: 0.544-0.574) with ordinal GS of PCa; and its mean, median and 10th percentile performed better than ADCs did in distinguishing LG from HG PCa. It is feasible to stratify the pathological grade of PCa by IVIM with histogram metrics. D performed better in distinguishing LG from HG tumour than conventional ADCs. • GS had relatively higher correlation with tumour D than ADCs. • Difference of histogram D among two-grade tumours was statistically significant. • D yielded better individual features in demonstrating tumour grade than ADC. • D* and f failed to determine tumour grade of PCa.

Detecting most influencing courses on students grades using block PCA

NASA Astrophysics Data System (ADS)

Othman, Osama H.; Gebril, Rami Salah

2014-12-01

One of the modern solutions adopted in dealing with the problem of large number of variables in statistical analyses is the Block Principal Component Analysis (Block PCA). This modified technique can be used to reduce the vertical dimension (variables) of the data matrix Xn×p by selecting a smaller number of variables, (say m) containing most of the statistical information. These selected variables can then be employed in further investigations and analyses. Block PCA is an adapted multistage technique of the original PCA. It involves the application of Cluster Analysis (CA) and variable selection throughout sub principal components scores (PC's). The application of Block PCA in this paper is a modified version of the original work of Liu et al (2002). The main objective was to apply PCA on each group of variables, (established using cluster analysis), instead of involving the whole large pack of variables which was proved to be unreliable. In this work, the Block PCA is used to reduce the size of a huge data matrix ((n = 41) × (p = 251)) consisting of Grade Point Average (GPA) of the students in 251 courses (variables) in the faculty of science in Benghazi University. In other words, we are constructing a smaller analytical data matrix of the GPA's of the students with less variables containing most variation (statistical information) in the original database. By applying the Block PCA, (12) courses were found to `absorb' most of the variation or influence from the original data matrix, and hence worth to be keep for future statistical exploring and analytical studies. In addition, the course Independent Study (Math.) was found to be the most influencing course on students GPA among the 12 selected courses.

Spectral discrimination of serum from liver cancer and liver cirrhosis using Raman spectroscopy

NASA Astrophysics Data System (ADS)

Yang, Tianyue; Li, Xiaozhou; Yu, Ting; Sun, Ruomin; Li, Siqi

2011-07-01

In this paper, Raman spectra of human serum were measured using Raman spectroscopy, then the spectra was analyzed by multivariate statistical methods of principal component analysis (PCA). Then linear discriminant analysis (LDA) was utilized to differentiate the loading score of different diseases as the diagnosing algorithm. Artificial neural network (ANN) was used for cross-validation. The diagnosis sensitivity and specificity by PCA-LDA are 88% and 79%, while that of the PCA-ANN are 89% and 95%. It can be seen that modern analyzing method is a useful tool for the analysis of serum spectra for diagnosing diseases.

Investigation of domain walls in PPLN by confocal raman microscopy and PCA analysis

NASA Astrophysics Data System (ADS)

Shur, Vladimir Ya.; Zelenovskiy, Pavel; Bourson, Patrice

2017-07-01

Confocal Raman microscopy (CRM) is a powerful tool for investigation of ferroelectric domains. Mechanical stresses and electric fields existed in the vicinity of neutral and charged domain walls modify frequency, intensity and width of spectral lines [1], thus allowing to visualize micro- and nanodomain structures both at the surface and in the bulk of the crystal [2,3]. Stresses and fields are naturally coupled in ferroelectrics due to inverse piezoelectric effect and hardly can be separated in Raman spectra. PCA is a powerful statistical method for analysis of large data matrix providing a set of orthogonal variables, called principal components (PCs). PCA is widely used for classification of experimental data, for example, in crystallization experiments, for detection of small amounts of components in solid mixtures etc. [4,5]. In Raman spectroscopy PCA was applied for analysis of phase transitions and provided critical pressure with good accuracy [6]. In the present work we for the first time applied Principal Component Analysis (PCA) method for analysis of Raman spectra measured in periodically poled lithium niobate (PPLN). We found that principal components demonstrate different sensitivity to mechanical stresses and electric fields in the vicinity of the domain walls. This allowed us to separately visualize spatial distribution of fields and electric fields at the surface and in the bulk of PPLN.

Subject order-independent group ICA (SOI-GICA) for functional MRI data analysis.

PubMed

Zhang, Han; Zuo, Xi-Nian; Ma, Shuang-Ye; Zang, Yu-Feng; Milham, Michael P; Zhu, Chao-Zhe

2010-07-15

Independent component analysis (ICA) is a data-driven approach to study functional magnetic resonance imaging (fMRI) data. Particularly, for group analysis on multiple subjects, temporally concatenation group ICA (TC-GICA) is intensively used. However, due to the usually limited computational capability, data reduction with principal component analysis (PCA: a standard preprocessing step of ICA decomposition) is difficult to achieve for a large dataset. To overcome this, TC-GICA employs multiple-stage PCA data reduction. Such multiple-stage PCA data reduction, however, leads to variable outputs due to different subject concatenation orders. Consequently, the ICA algorithm uses the variable multiple-stage PCA outputs and generates variable decompositions. In this study, a rigorous theoretical analysis was conducted to prove the existence of such variability. Simulated and real fMRI experiments were used to demonstrate the subject-order-induced variability of TC-GICA results using multiple PCA data reductions. To solve this problem, we propose a new subject order-independent group ICA (SOI-GICA). Both simulated and real fMRI data experiments demonstrated the high robustness and accuracy of the SOI-GICA results compared to those of traditional TC-GICA. Accordingly, we recommend SOI-GICA for group ICA-based fMRI studies, especially those with large data sets. Copyright 2010 Elsevier Inc. All rights reserved.

PBOV1 as a potential biomarker for more advanced prostate cancer based on protein and digital histomorphometric analysis.

PubMed

Carleton, Neil M; Zhu, Guangjing; Gorbounov, Mikhail; Miller, M Craig; Pienta, Kenneth J; Resar, Linda M S; Veltri, Robert W

2018-05-01

There are few tissue-based biomarkers that can accurately predict prostate cancer (PCa) progression and aggressiveness. We sought to evaluate the clinical utility of prostate and breast overexpressed 1 (PBOV1) as a potential PCa biomarker. Patient tumor samples were designated by Grade Groups using the 2014 Gleason grading system. Primary radical prostatectomy tumors were obtained from 48 patients and evaluated for PBOV1 levels using Western blot analysis in matched cancer and benign cancer-adjacent regions. Immunohistochemical evaluation of PBOV1 was subsequently performed in 80 cancer and 80 benign cancer-adjacent patient samples across two tissue microarrays (TMAs) to verify protein levels in epithelial tissue and to assess correlation between PBOV1 proteins and nuclear architectural changes in PCa cells. Digital histomorphometric analysis was used to track 22 parameters that characterized nuclear changes in PBOV1-stained cells. Using a training and test set for validation, multivariate logistic regression (MLR) models were used to identify significant nuclear parameters that distinguish Grade Group 3 and above PCa from Grade Group 1 and 2 PCa regions. PBOV1 protein levels were increased in tumors from Grade Group 3 and above (GS 4 + 3 and ≥ 8) regions versus Grade Groups 1 and 2 (GS 3 + 3 and 3 + 4) regions (P = 0.005) as assessed by densitometry of immunoblots. Additionally, by immunoblotting, PBOV1 protein levels differed significantly between Grade Group 2 (GS 3 + 4) and Grade Group 3 (GS 4 + 3) PCa samples (P = 0.028). In the immunohistochemical analysis, measures of PBOV1 staining intensity strongly correlated with nuclear alterations in cancer cells. An MLR model retaining eight parameters describing PBOV1 staining intensity and nuclear architecture discriminated Grade Group 3 and above PCa from Grade Group 1 and 2 PCa and benign cancer-adjacent regions with a ROC-AUC of 0.90 and 0.80, respectively, in training and test sets. Our study demonstrates that the PBOV1 protein could be used to discriminate Grade Group 3 and above PCa. Additionally, the PBOV1 protein could be involved in modulating changes to the nuclear architecture of PCa cells. Confirmatory studies are warranted in an independent population for further validation. © 2018 Wiley Periodicals, Inc.

Interval to Testosterone Recovery After Hormonal Therapy for Prostate Cancer and Risk of Death

DOE Office of Scientific and Technical Information (OSTI.GOV)

D'Amico, Anthony V.; Chen, M.-H.; Renshaw, Andrew A.

Purpose: To assess whether the risk of death is associated with the time to testosterone recovery (TTR) after radiotherapy (RT) and hormonal therapy (HT) for prostate cancer (PCa). Patients and Methods: Between 1995 and 2001, 206 men with localized, unfavorable-risk PCa were randomized to receive RT or RT plus 6 months of HT. A multivariate postrandomization Cox regression analysis was used to assess whether the TTR in years was associated with the risk of death after adjusting for the known prognostic factors, age, Adult Comorbidity Evaluation-27 score, and the use of HT for recurrence. Results: Of the 102 men randomizedmore » to receive RT and HT, 57 (56%) had a TTR of >2 years, and none of these men had died of PCa after a median follow-up of 7.6 years. As the TTR increased, the risk of death decreased significantly (adjusted hazard ratio, 0.60; 95% confidence interval, 0.43-0.84; p = .003). A significant interaction was noted between the TTR and the comorbidity score (p = .002). The survival estimates were similar (p = 0.17) across the TTR values in men with moderate to severe comorbidity; however, these estimates increased significantly (p < .001) with decreasing PCa-specific mortality (p = .006) as the TTR increased in men with no or minimal comorbidity. Conclusion: The results of our study have shown that a longer TTR after RT plus 6 months of HT for unfavorable-risk PCa is associated with a lower risk of death in men with no or minimal comorbidity.« less

Discrimination of liver cancer in cellular level based on backscatter micro-spectrum with PCA algorithm and BP neural network

NASA Astrophysics Data System (ADS)

Yang, Jing; Wang, Cheng; Cai, Gan; Dong, Xiaona

2016-10-01

The incidence and mortality rate of the primary liver cancer are very high and its postoperative metastasis and recurrence have become important factors to the prognosis of patients. Circulating tumor cells (CTC), as a new tumor marker, play important roles in the early diagnosis and individualized treatment. This paper presents an effective method to distinguish liver cancer based on the cellular scattering spectrum, which is a non-fluorescence technique based on the fiber confocal microscopic spectrometer. Combining the principal component analysis (PCA) with back propagation (BP) neural network were utilized to establish an automatic recognition model for backscatter spectrum of the liver cancer cells from blood cell. PCA was applied to reduce the dimension of the scattering spectral data which obtained by the fiber confocal microscopic spectrometer. After dimensionality reduction by PCA, a neural network pattern recognition model with 2 input layer nodes, 11 hidden layer nodes, 3 output nodes was established. We trained the network with 66 samples and also tested it. Results showed that the recognition rate of the three types of cells is more than 90%, the relative standard deviation is only 2.36%. The experimental results showed that the fiber confocal microscopic spectrometer combining with the algorithm of PCA and BP neural network can automatically identify the liver cancer cell from the blood cells. This will provide a better tool for investigating the metastasis of liver cancers in vivo, the biology metabolic characteristics of liver cancers and drug transportation. Additionally, it is obviously referential in practical application.

Small molecule screening reveals a transcription-independent pro-survival function of androgen receptor in castration-resistant prostate cancer

PubMed Central

Narizhneva, Natalia V.; Tararova, Natalia D.; Ryabokon, Petro; Shyshynova, Inna; Prokvolit, Anatoly; Komarov, Pavel G.; Purmal, Andrei A.; Gudkov, Andrei V.; Gurova, Katerina V.

2010-01-01

In prostate cancer (PCa) patients, initial responsiveness to androgen deprivation therapy is frequently followed by relapse due to development of treatment-resistant androgen-independent PCa. This is typically associated with acquisition of mutations in AR that allow activity as a transcription factor in the absence of ligand, indicating that androgen-independent PCa remains dependent on AR function. Our strategy to effectively target AR in androgen-independent PCa involved using a cell-based readout to isolate small molecules that inhibit AR transactivation function through mechanisms other than modulation of ligand binding. A number of the identified inhibitors were toxic to AR-expressing PCa cells regardless of their androgen dependence. Among these, some only suppressed PCa cell growth (ARTIS), while others induced cell death (ARTIK). ARTIK, but not ARTIS, compounds caused disappearance of AR protein from treated cells. siRNA against AR behaved like ARTIK compounds, while a dominant negative AR mutant that prevents AR-mediated transactivation but does not eliminate the protein showed only a growth suppressive effect. These observations reveal a transcription-independent function of AR that is essential for PCa cell viability and, therefore, is an ideal target for anti-PCa treatment. Indeed, several of the identified AR inhibitors demonstrated in vivo efficacy in mouse models of PCa and are candidates for pharmacologic optimization. PMID:19946220

Clustering of metabolic and cardiovascular risk factors in the polycystic ovary syndrome: a principal component analysis.

PubMed

Stuckey, Bronwyn G A; Opie, Nicole; Cussons, Andrea J; Watts, Gerald F; Burke, Valerie

2014-08-01

Polycystic ovary syndrome (PCOS) is a prevalent condition with heterogeneity of clinical features and cardiovascular risk factors that implies multiple aetiological factors and possible outcomes. To reduce a set of correlated variables to a smaller number of uncorrelated and interpretable factors that may delineate subgroups within PCOS or suggest pathogenetic mechanisms. We used principal component analysis (PCA) to examine the endocrine and cardiometabolic variables associated with PCOS defined by the National Institutes of Health (NIH) criteria. Data were retrieved from the database of a single clinical endocrinologist. We included women with PCOS (N = 378) who were not taking the oral contraceptive pill or other sex hormones, lipid lowering medication, metformin or other medication that could influence the variables of interest. PCA was performed retaining those factors with eigenvalues of at least 1.0. Varimax rotation was used to produce interpretable factors. We identified three principal components. In component 1, the dominant variables were homeostatic model assessment (HOMA) index, body mass index (BMI), high density lipoprotein (HDL) cholesterol and sex hormone binding globulin (SHBG); in component 2, systolic blood pressure, low density lipoprotein (LDL) cholesterol and triglycerides; in component 3, total testosterone and LH/FSH ratio. These components explained 37%, 13% and 11% of the variance in the PCOS cohort respectively. Multiple correlated variables from patients with PCOS can be reduced to three uncorrelated components characterised by insulin resistance, dyslipidaemia/hypertension or hyperandrogenaemia. Clustering of risk factors is consistent with different pathogenetic pathways within PCOS and/or differing cardiometabolic outcomes. Copyright © 2014 Elsevier Inc. All rights reserved.

Physicochemical and mechanical properties of paracetamol cocrystal with 5-nitroisophthalic acid.

PubMed

Hiendrawan, Stevanus; Veriansyah, Bambang; Widjojokusumo, Edward; Soewandhi, Sundani Nurono; Wikarsa, Saleh; Tjandrawinata, Raymond R

2016-01-30

We report novel pharmaceutical cocrystal of a popular antipyretic drug paracetamol (PCA) with coformer 5-nitroisophhthalic acid (5NIP) to improve its tabletability. The cocrystal (PCA-5NIP at molar ratio of 1:1) was synthesized by solvent evaporation technique using methanol as solvent. The physicochemical properties of cocrystal were characterized by powder X-ray diffraction (PXRD), differential scanning calorimetry (DSC), thermogravimetry analysis (TGA), fourier transform infrared spectroscopy (FTIR), hot stage polarized microscopy (HSPM) and scanning electron microscopy (SEM). Stability of the cocrystal was assessed by storing them at 40°C/75% RH for one month. Compared to PCA, the cocrystal displayed superior tableting performance. PCA-5NIP cocrystal showed a similar dissolution profile as compared to PCA and exhibited good stability. This study showed the utility of PCA-5NIP cocrystal for improving mechanical properties of PCA. Copyright © 2015 Elsevier B.V. All rights reserved.

PEM-PCA: a parallel expectation-maximization PCA face recognition architecture.

PubMed

Rujirakul, Kanokmon; So-In, Chakchai; Arnonkijpanich, Banchar

2014-01-01

Principal component analysis or PCA has been traditionally used as one of the feature extraction techniques in face recognition systems yielding high accuracy when requiring a small number of features. However, the covariance matrix and eigenvalue decomposition stages cause high computational complexity, especially for a large database. Thus, this research presents an alternative approach utilizing an Expectation-Maximization algorithm to reduce the determinant matrix manipulation resulting in the reduction of the stages' complexity. To improve the computational time, a novel parallel architecture was employed to utilize the benefits of parallelization of matrix computation during feature extraction and classification stages including parallel preprocessing, and their combinations, so-called a Parallel Expectation-Maximization PCA architecture. Comparing to a traditional PCA and its derivatives, the results indicate lower complexity with an insignificant difference in recognition precision leading to high speed face recognition systems, that is, the speed-up over nine and three times over PCA and Parallel PCA.

Interaction of Soil Heavy Metal Pollution with Industrialisation and the Landscape Pattern in Taiyuan City, China

PubMed Central

Liu, Yong; Su, Chao; Zhang, Hong; Li, Xiaoting; Pei, Jingfei

2014-01-01

Many studies indicated that industrialization and urbanization caused serious soil heavy metal pollution from industrialized age. However, fewer previous studies have conducted a combined analysis of the landscape pattern, urbanization, industrialization, and heavy metal pollution. This paper was aimed at exploring the relationships of heavy metals in the soil (Pb, Cu, Ni, As, Cd, Cr, Hg, and Zn) with landscape pattern, industrialisation, urbanisation in Taiyuan city using multivariate analysis. The multivariate analysis included correlation analysis, analysis of variance (ANOVA), independent-sample T test, and principal component analysis (PCA). Geographic information system (GIS) was also applied to determine the spatial distribution of the heavy metals. The spatial distribution maps showed that the heavy metal pollution of the soil was more serious in the centre of the study area. The results of the multivariate analysis indicated that the correlations among heavy metals were significant, and industrialisation could significantly affect the concentrations of some heavy metals. Landscape diversity showed a significant negative correlation with the heavy metal concentrations. The PCA showed that a two-factor model for heavy metal pollution, industrialisation, and the landscape pattern could effectively demonstrate the relationships between these variables. The model explained 86.71% of the total variance of the data. Moreover, the first factor was mainly loaded with the comprehensive pollution index (P), and the second factor was primarily loaded with landscape diversity and dominance (H and D). An ordination of 80 samples could show the pollution pattern of all the samples. The results revealed that local industrialisation caused heavy metal pollution of the soil, but such pollution could respond negatively to the landscape pattern. The results of the study could provide a basis for agricultural, suburban, and urban planning. PMID:25251460

Interaction of soil heavy metal pollution with industrialisation and the landscape pattern in Taiyuan city, China.

PubMed

Liu, Yong; Su, Chao; Zhang, Hong; Li, Xiaoting; Pei, Jingfei

2014-01-01

Many studies indicated that industrialization and urbanization caused serious soil heavy metal pollution from industrialized age. However, fewer previous studies have conducted a combined analysis of the landscape pattern, urbanization, industrialization, and heavy metal pollution. This paper was aimed at exploring the relationships of heavy metals in the soil (Pb, Cu, Ni, As, Cd, Cr, Hg, and Zn) with landscape pattern, industrialisation, urbanisation in Taiyuan city using multivariate analysis. The multivariate analysis included correlation analysis, analysis of variance (ANOVA), independent-sample T test, and principal component analysis (PCA). Geographic information system (GIS) was also applied to determine the spatial distribution of the heavy metals. The spatial distribution maps showed that the heavy metal pollution of the soil was more serious in the centre of the study area. The results of the multivariate analysis indicated that the correlations among heavy metals were significant, and industrialisation could significantly affect the concentrations of some heavy metals. Landscape diversity showed a significant negative correlation with the heavy metal concentrations. The PCA showed that a two-factor model for heavy metal pollution, industrialisation, and the landscape pattern could effectively demonstrate the relationships between these variables. The model explained 86.71% of the total variance of the data. Moreover, the first factor was mainly loaded with the comprehensive pollution index (P), and the second factor was primarily loaded with landscape diversity and dominance (H and D). An ordination of 80 samples could show the pollution pattern of all the samples. The results revealed that local industrialisation caused heavy metal pollution of the soil, but such pollution could respond negatively to the landscape pattern. The results of the study could provide a basis for agricultural, suburban, and urban planning.

Bidding factors-the reduction of the data dimension with the use of PCA

NASA Astrophysics Data System (ADS)

Leśniak, Agnieszka

2017-07-01

Making the decision to participate in the tender is subject to a number of factors, affects the health of the company and is an important aspect in its quest for success. Efforts to select bidding factors have been repeatedly undertaken in various countries and in numerous construction markets. Researchers usually give a long list of factors, also called criteria, which in their opinion may significantly influence the bidding decision. The paper presents an attempt to reduce a proposed set of bidding factorsdefined in Poland with the use of thePrincipal Component Analysis.

Kallikrein 3 and vitamin D receptor polymorphisms: potentials environmental risk factors for prostate cancer

PubMed Central

2014-01-01

Objective To investigate the relationship and interaction of the single nucleotide polymorphisms (SNPs) of KLK3 and VDR and environmental factors with the predisposition to prostate cancer within Chinese population. Methods The comparison between 108 patients and 242 healthy people was carried out by using the TaqMan/MGB Probe Technology to determine the genotypes of KLK3(rs2735839 is located between KLK2 and KLK3) and VDR (rs731236 is located exon 9). Univariate and multivariate logistic regression model were used to assess the connection of genetic polymorphisms and environmental risk factors with PCa by collecting demographic information, as well as BMI, consumption of cigarettes, alcohol, and tea, exercise, and other environmental risk factors. Results The appearing frequencies of AA, AG, and GG genotypes at the SNPs rs2735839 (A/G) for KLK3 were 13.89%, 62.96% and 23.15% in PCa and 37.19%, 44.63%, 18.18% in control, respectively; these two groups are statistically different (P = 0.00). While the appearing frequencies of TT, TC, and CC genotypes at the SNPs rs731236 (T/C) for VDR were 88.89%, 9, 26%, 1.85% and 90.50%, 9.10%, 0.40% in control, respectively, with no significant statistical difference between the two group. The study confirmed decreasing risk in tea drinkers (OR = 0.58, 95% CI = 0.35-0.96). Conclusions Our studies indicate that environmental factor-tea drinking is associated with the development of PCa. The habit of drinking tea is a protective factor against PCa. The SNPs rs2735839 for KLK3 is strongly related to the development of PCa, while the SNPs rs731236 for VDR is not. Virtual slides The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/9759981571058803. PMID:24755043

Kernel Principal Component Analysis for dimensionality reduction in fMRI-based diagnosis of ADHD.

PubMed

Sidhu, Gagan S; Asgarian, Nasimeh; Greiner, Russell; Brown, Matthew R G

2012-01-01

This study explored various feature extraction methods for use in automated diagnosis of Attention-Deficit Hyperactivity Disorder (ADHD) from functional Magnetic Resonance Image (fMRI) data. Each participant's data consisted of a resting state fMRI scan as well as phenotypic data (age, gender, handedness, IQ, and site of scanning) from the ADHD-200 dataset. We used machine learning techniques to produce support vector machine (SVM) classifiers that attempted to differentiate between (1) all ADHD patients vs. healthy controls and (2) ADHD combined (ADHD-c) type vs. ADHD inattentive (ADHD-i) type vs. controls. In different tests, we used only the phenotypic data, only the imaging data, or else both the phenotypic and imaging data. For feature extraction on fMRI data, we tested the Fast Fourier Transform (FFT), different variants of Principal Component Analysis (PCA), and combinations of FFT and PCA. PCA variants included PCA over time (PCA-t), PCA over space and time (PCA-st), and kernelized PCA (kPCA-st). Baseline chance accuracy was 64.2% produced by guessing healthy control (the majority class) for all participants. Using only phenotypic data produced 72.9% accuracy on two class diagnosis and 66.8% on three class diagnosis. Diagnosis using only imaging data did not perform as well as phenotypic-only approaches. Using both phenotypic and imaging data with combined FFT and kPCA-st feature extraction yielded accuracies of 76.0% on two class diagnosis and 68.6% on three class diagnosis-better than phenotypic-only approaches. Our results demonstrate the potential of using FFT and kPCA-st with resting-state fMRI data as well as phenotypic data for automated diagnosis of ADHD. These results are encouraging given known challenges of learning ADHD diagnostic classifiers using the ADHD-200 dataset (see Brown et al., 2012).

Using the prostate imaging reporting and data system version 2 (PI-RIDS v2) to detect prostate cancer can prevent unnecessary biopsies and invasive treatment.

PubMed

Liu, Chang; Liu, Shi-Liang; Wang, Zhi-Xian; Yu, Kai; Feng, Chun-Xiang; Ke, Zan; Wang, Liang; Zeng, Xiao-Yong

2018-04-13

Prostate cancer (PCa) is one of the most common cancers among men globally. The authors aimed to evaluate the ability of the Prostate Imaging Reporting and Data System version 2 (PI-RADS v2) to classify men with PCa, clinically significant PCa (CSPCa), or no PCa, especially among those with serum total prostate-specific antigen (tPSA) levels in the "gray zone" (4-10 ng ml -1 ). A total of 308 patients (355 lesions) were enrolled in this study. Diagnostic efficiency was determined. Univariate and multivariate analyses, receiver operating characteristic curve analysis, and decision curve analysis were performed to determine and compare the predictors of PCa and CSPCa. The results suggested that PI-RADS v2, tPSA, and prostate-specific antigen density (PSAD) were independent predictors of PCa and CSPCa. A PI-RADS v2 score ≥4 provided high negative predictive values (91.39% for PCa and 95.69% for CSPCa). A model of PI-RADS combined with PSA and PSAD helped to define a high-risk group (PI-RADS score = 5 and PSAD ≥0.15 ng ml -1 cm -3 , with tPSA in the gray zone, or PI-RADS score ≥4 with high tPSA level) with a detection rate of 96.1% for PCa and 93.0% for CSPCa while a low-risk group with a detection rate of 6.1% for PCa and 2.2% for CSPCa. It was concluded that the PI-RADS v2 could be used as a reliable and independent predictor of PCa and CSPCa. The combination of PI-RADS v2 score with PSA and PSAD could be helpful in the prediction and diagnosis of PCa and CSPCa and, thus, may help in preventing unnecessary invasive procedures.

Prognostic Value of Neutrophil-to-Lymphocyte Ratio in Localized and Advanced Prostate Cancer: A Systematic Review and Meta-Analysis.

PubMed

Tang, Lu; Li, Xintao; Wang, Baojun; Luo, Guoxiong; Gu, Liangyou; Chen, Luyao; Liu, Kan; Gao, Yu; Zhang, Xu

2016-01-01

Increasing evidence suggests that inflammation plays an essential role in cancer development and progression. The inflammation marker neutrophil-lymphocyte ratio (NLR) is correlated with prognosis across a wide variety of tumor types, but its prognostic value in prostate cancer (PCa) remains controversial. In the present meta-analysis, the prognostic value of NLR in PCa patients is investigated. We performed a meta-analysis to determine the predictive value of NLR for overall survival (OS), recurrence-free survival (RFS), and clinical features in patients with PCa. We systematically searched PubMed, ISI Web of Science, and Embase for relevant studies published up to October 2015. A total of 9418 patients from 18 studies were included in the meta-analysis. Elevated pretreatment NLR predicted poor OS (HR 1.628, 95% CI 1.410-1.879) and RFS (HR 1.357, 95% CI 1.126-1.636) in all patients with PCa. However, NLR was insignificantly associated with OS in the subgroup of patients with localized PCa (HR 1.439, 95% CI 0.753-2.75). Increased NLR was also significantly correlated with lymph node involvement (OR 1.616, 95% CI 1.167-2.239) but not with pathological stage (OR 0.827, 95% CI 0.637-1.074) or Gleason score (OR 0.761, 95% CI 0.555-1.044). The present meta-analysis indicated that NLR could predict the prognosis for patients with locally advanced or castration-resistant PCa. Patients with higher NLR are more likely to have poorer prognosis than those with lower NLR.

Minireview: The Molecular and Genomic Basis for Prostate Cancer Health Disparities

PubMed Central

Bollig-Fischer, Aliccia

2013-01-01

Despite more aggressive screening across all demographics and gradual declines in mortality related to prostate cancer (PCa) in the United States, race disparities persist. For African American men (AAM), PCa is more often an aggressive disease showing increased metastases and greater PCa-related mortality compared with European American men. The earliest research points to how distinctions are likely the result of a combination of factors, including ancestry genetics and lifestyle variables. More recent research considers that cancer, although influenced by external forces, is ultimately a disease primarily driven by aberrations observed in the molecular genetics of the tumor. Research studying PCa predominantly from European American men shows that indolent and advanced or metastatic prostate tumors have distinguishing molecular genomic make-ups. Early yet increasing evidence suggests that clinically distinct PCa from AAM also display molecular distinctions. It is reasonable to predict that further study will reveal molecular subtypes and various frequencies for PCa subtypes among diverse patient groups, thereby providing insight as to the genomic lesions and gene signatures that are functionally implicated in carcinogenesis or aggressive PCa in AAM. That knowledge will prove useful in developing strategies to predict who will develop advanced PCa among AAM and will provide the rationale to develop effective individualized treatment strategies to overcome disparities. PMID:23608645

Clonazepam treatment of pathologic childhood aerophagia with psychological stresses.

PubMed

Hwang, Jin Bok; Kim, Jun Sik; Ahn, Byung Hoon; Jung, Chul Ho; Lee, Young Hwan; Kam, Sin

2007-04-01

The treatment of pathologic aerophagia has rarely been discussed in the literature. In this retrospective study, the authors investigated the effects of clonazepam on the management of pathologic childhood aerophagia (PCA) with psychological stresses (PS), but not with mental retardation. Data from 22 consecutive PCA patients with PS (aged 2 to 10 yr), who had been followed up for over 1 yr, were reviewed. On the basis of videolaryngoscopic views, the authors observed that the pathology of aerophagia was the result of reflex-induced swallowing with paroxysmal openings of the upper esophageal sphincter due to unknown factors and also observed that these reflex-induced openings were subsided after intravenous low dose benzodiazepine administration. Hence, clonazepam was administered to treat paroxysmal openings in these PCA patients with PS. Remission positivity was defined as symptom-free for a consecutive 1 month within 6 months of treatment. The results of treatment in 22 PCA patients with PS were analyzed. A remission positive state was documented in 14.3% of PCA patients managed by reassurance, and in 66.7% of PCA patients treated with clonazepam (p=0.032). Thus, clonazepam may produce positive results in PCA with PS. Future studies by randomized and placebo-controlled trials are needed to confirm the favorable effect of clonazepam in PCA.

Clonazepam Treatment of Pathologic Childhood Aerophagia with Psychological Stresses

PubMed Central

Kim, Jun Sik; Ahn, Byung Hoon; Jung, Chul-Ho; Lee, Young Hwan; Kam, Sin

2007-01-01

The treatment of pathologic aerophagia has rarely been discussed in the literature. In this retrospective study, the authors investigated the effects of clonazepam on the management of pathologic childhood aerophagia (PCA) with psychological stresses (PS), but not with mental retardation. Data from 22 consecutive PCA patients with PS (aged 2 to 10 yr), who had been followed up for over 1 yr, were reviewed. On the basis of videolaryngoscopic views, the authors observed that the pathologyof aerophagia was the result of reflex-induced swallowing with paroxysmal openings of the upper esophageal sphincter due to unknown factors and also observed that these reflex-induced openings were subsided after intravenous low dose benzodiazepine administration. Hence, clonazepam was administered to treat paroxysmal openings in these PCA patients with PS. Remission positivity was defined as symptom-free for a consecutive 1 month within 6 months of treatment. The results of treatment in 22 PCA patients with PS were analyzed. A remission positive state was documented in 14.3% of PCA patients managed by reassurance, and in 66.7% of PCA patients treated with clonazepam (p=0.032). Thus, clonazepam may produce positive results in PCA with PS. Future studies by randomized and placebo-controlled trials are needed to confirm the favorable effect of clonazepam in PCA. PMID:17449924

Tumour-derived alkaline phosphatase regulates tumour growth, epithelial plasticity and disease-free survival in metastatic prostate cancer

PubMed Central

Rao, S R; Snaith, A E; Marino, D; Cheng, X; Lwin, S T; Orriss, I R; Hamdy, F C; Edwards, C M

2017-01-01

Background: Recent evidence suggests that bone-related parameters are the main prognostic factors for overall survival in advanced prostate cancer (PCa), with elevated circulating levels of alkaline phosphatase (ALP) thought to reflect the dysregulated bone formation accompanying distant metastases. We have identified that PCa cells express ALPL, the gene that encodes for tissue nonspecific ALP, and hypothesised that tumour-derived ALPL may contribute to disease progression. Methods: Functional effects of ALPL inhibition were investigated in metastatic PCa cell lines. ALPL gene expression was analysed from published PCa data sets, and correlated with disease-free survival and metastasis. Results: ALPL expression was increased in PCa cells from metastatic sites. A reduction in tumour-derived ALPL expression or ALP activity increased cell death, mesenchymal-to-epithelial transition and reduced migration. Alkaline phosphatase activity was decreased by the EMT repressor Snail. In men with PCa, tumour-derived ALPL correlated with EMT markers, and high ALPL expression was associated with a significant reduction in disease-free survival. Conclusions: Our studies reveal the function of tumour-derived ALPL in regulating cell death and epithelial plasticity, and demonstrate a strong association between ALPL expression in PCa cells and metastasis or disease-free survival, thus identifying tumour-derived ALPL as a major contributor to the pathogenesis of PCa progression. PMID:28006818

The Burden of Urinary Incontinence and Urinary Bother Among Elderly Prostate Cancer Survivors

PubMed Central

Kopp, Ryan P.; Marshall, Lynn M.; Wang, Patty Y.; Bauer, Douglas C.; Barrett-Connor, Elizabeth; Parsons, J. Kellogg

2014-01-01

Background Data describing urinary health in elderly, community-dwelling prostate cancer (PCa) survivors are limited. Objective To elucidate the prevalence of lower urinary tract symptoms, urinary bother, and incontinence in elderly PCa survivors compared with peers without PCa. Design, setting, and participants A cross-sectional analysis of 5990 participants in the Osteoporotic Fractures in Men Research Group, a cohort study of community-dwelling men ≥65 yr. Outcome measurements and statistical analysis We characterized urinary health using self-reported urinary incontinence and the American Urological Association Symptom Index (AUA-SI). We compared urinary health measures according to type of PCa treatment in men with PCa and men without PCa using multivariate log-binomial regression to generate prevalence ratios (PRs). Results and limitations At baseline, 706 men (12%) reported a history of PCa, with a median time since diagnosis of 6.3 yr. Of these men, 426 (60%) reported urinary incontinence. In adjusted analyses, observation (PR: 1.92; 95% confidence interval [CI], 1.15–3.21; p = 0.01), surgery (PR: 4.68; 95% CI, 4.11–5.32; p < 0.0001), radiation therapy (PR: 1.64; 95% CI, 1.20– 2.23; p = 0.002), and androgen-deprivation therapy (ADT) (PR: 2.01; 95% CI, 1.35–2.99; p = 0.0006) were each associated with daily incontinence. Daily incontinence risk increased with time since diagnosis independently of age. Observation (PR: 1.33; 95% CI, 1.00–1.78; p = 0.05), surgery (PR: 1.25; 95% CI, 1.10–1.42; p = 0.0008), and ADT (PR: 1.50; 95% CI, 1.26–1.79; p < 0.0001) were associated with increased AUA-SI bother scores. Cancer stage and use of adjuvant or salvage therapies were not available for analysis. Conclusions Compared with their peers without PCa, elderly PCa survivors had a two-fold to five-fold greater prevalence of urinary incontinence, which rose with increasing survivorship duration. Observation, surgery, and ADT were each associated with increased urinary bother. These data suggest a substantially greater burden of urinary health problems among elderly PCa survivors than previously recognized. PMID:23587870

Qualitative analysis of precipitate formation on the surface and in the tubules of dentin irrigated with sodium hypochlorite and a final rinse of chlorhexidine or QMiX.

PubMed

Kolosowski, Kamil P; Sodhi, Rana N S; Kishen, Anil; Basrani, Bettina R

2014-12-01

Interaction of sodium hypochlorite (NaOCl) mixed with chlorhexidine (CHX) produces a brown precipitate containing para-chloroaniline (PCA). When QMiX is mixed with NaOCl, no precipitate forms, but color change occurs. The aim of this study was to qualitatively assess the formation of precipitate and PCA on the surface and in the tubules of dentin irrigated with NaOCl, followed either by EDTA, NaOCl, and CHX or by saline and QMiX by using time-of-flight secondary ion mass spectrometry (TOF-SIMS). Dentin blocks were obtained from human maxillary molars, embedded in resin, and cross-sectioned to expose dentin. Specimens in group 1 were immersed in 2.5% NaOCl, followed by 17% EDTA, 2.5% NaOCl, and 2% CHX. Specimens in group 2 were immersed in 2.5% NaOCl, followed by saline and QMiX. The dentin surfaces were subjected to TOF-SIMS spectra analysis. Longitudinal sections of dentin blocks were then exposed and subjected to TOF-SIMS analysis. All samples and analysis were performed in triplicate for confirmation. TOF-SIMS analysis of group 1 revealed an irregular precipitate, containing PCA and CHX breakdown products, on the dentin surfaces, occluding and extending into the tubules. In TOF-SIMS analysis of group 2, no precipitates, including PCA, were detected on the dentin surface or in the tubules. Within the limitations of this study, precipitate containing PCA was formed in the tubules of dentin irrigated with NaOCl followed by CHX. No precipitates or PCA were detected in the tubules of dentin irrigated with NaOCl followed by saline and QMiX. Copyright © 2014 American Association of Endodontists. Published by Elsevier Inc. All rights reserved.

Relationships between of Sea Urchins Abundance, Macroalgae and Coral Closure on the Cemara Kecil island

NASA Astrophysics Data System (ADS)

Suryanti, Suryanti; Ain, Churun; Latifah, Nurul

2018-05-01

Sea urchins are one of the key species for coral reef communities because have the capability for controlling populations of microalgae. The existence of sea urchins in an waters ecosystem influenced by abiotic and biotic environmental factors such as intraspecific or intraspecific interactions. This study aims to determine the relationship between the abundance of Sea Urchins, Macroalga on massive coral, and coral cover on Cemara Kecil Island by PCA analysis. The study was conducted in May 2017 in Cemara Kecil Island. Method of research with Haphazard sampling technique. The results indicate that numbers of sea urchins found ranges from 78-130 ind/m2, an abundance of macroalgae found are Sargassum sp 1.36%, Caulerpa sp.7.43% and Padina sp 91.21%. The results of substrate cover are living coral 47,21%, dead coral 23.33%, other fauna 2.85% and abiotic element 26,61%. Based on the results of PCA analysis that Sea Urchin abundance has a positive correlation with the closure of Coral Reef and Caulerpa sp. While the Padina sp and Sargassum sp have a positive correlation as well as abiotic factors, dead coral, and other fauna.

Assessment of metal pollution based on multivariate statistical modeling of 'hot spot' sediments from the Black Sea.

PubMed

Simeonov, V; Massart, D L; Andreev, G; Tsakovski, S

2000-11-01

The paper deals with application of different statistical methods like cluster and principal components analysis (PCA), partial least squares (PLSs) modeling. These approaches are an efficient tool in achieving better understanding about the contamination of two gulf regions in Black Sea. As objects of the study, a collection of marine sediment samples from Varna and Bourgas "hot spots" gulf areas are used. In the present case the use of cluster and PCA make it possible to separate three zones of the marine environment with different levels of pollution by interpretation of the sediment analysis (Bourgas gulf, Varna gulf and lake buffer zone). Further, the extraction of four latent factors offers a specific interpretation of the possible pollution sources and separates natural from anthropogenic factors, the latter originating from contamination by chemical, oil refinery and steel-work enterprises. Finally, the PLSs modeling gives a better opportunity in predicting contaminant concentration on tracer (or tracers) element as compared to the one-dimensional approach of the baseline models. The results of the study are important not only in local aspect as they allow quick response in finding solutions and decision making but also in broader sense as a useful environmetrical methodology.

Germline Mutations in ATM and BRCA1/2 Distinguish Risk for Lethal and Indolent Prostate Cancer and are Associated with Early Age at Death

PubMed Central

Na, Rong; Zheng, S. Lilly; Han, Misop; Yu, Hongjie; Jiang, Deke; Shah, Sameep; Ewing, Charles M.; Zhang, Liti; Novakovic, Kristian; Petkewicz, Jacqueline; Gulukota, Kamalakar; Helseth, Donald L.; Quinn, Margo; Humphries, Elizabeth; Wiley, Kathleen E.; Isaacs, Sarah D.; Wu, Yishuo; Liu, Xu; Zhang, Ning; Wang, Chi-Hsiung; Khandekar, Janardan; Hulick, Peter J.; Shevrin, Daniel H.; Cooney, Kathleen A.; Shen, Zhoujun; Partin, Alan W.; Carter, H. Ballentine; Carducci, Michael A.; Eisenberger, Mario A.; Denmeade, Sam R.; McGuire, Michael; Walsh, Patrick C.; Helfand, Brian T.; Brendler, Charles B.; Ding, Qiang; Xu, Jianfeng; Isaacs, William B.

2017-01-01

Background Germline mutations in BRCA1/2 and ATM have been associated with prostate cancer (PCa) risk. Objective To directly assess whether germline mutations in these three genes distinguish lethal from indolent PCa and whether they confer any effect on age at death. Design, setting, and participants A retrospective case-case study of 313 patients who died of PCa and 486 patients with low-risk localized PCa of European, African, and Chinese descent. Germline DNA of each of the 799 patients was sequenced for these three genes. Outcome measurements and statistical analysis Mutation carrier rates and their effect on lethal PCa were analyzed using the Fisher’s exact test and Cox regression analysis, respectively. Results and limitations The combined BRCA1/2 and ATM mutation carrier rate was significantly higher in lethal PCa patients (6.07%) than localized PCa patients (1.44%), p = 0.0007. The rate also differed significantly among lethal PCa patients as a function of age at death (10.00%, 9.08%, 8.33%, 4.94%, and 2.97% in patients who died ≤60 yr, 61–65 yr, 66–70 yr, 71–75 yr, and over 75 yr, respectively, p = 0.046) and time to death after diagnosis (12.26%, 4.76%, and 0.98% in patients who died ≤5 yr, 6–10 yr, and > 10 yr after a PCa diagnosis, respectively, p = 0.0006). Survival analysis in the entire cohort revealed mutation carriers remained an independent predictor of lethal PCa after adjusting for race and age, prostate-specific antigen, and Gleason score at the time of diagnosis (hazard ratio = 2.13, 95% confidence interval: 1.24–3.66, p = 0.004). A limitation of this study is that other DNA repair genes were not analyzed. Conclusions Mutation status of BRCA1/2 and ATM distinguishes risk for lethal and indolent PCa and is associated with earlier age at death and shorter survival time. Patient summary Prostate cancer patients with inherited mutations in BRCA1/2 and ATM are more likely to die of prostate cancer and do so at an earlier age. PMID:27989354

Prolactin- and testosterone-induced carboxypeptidase-D correlates with increased nitrotyrosines and Ki67 in prostate cancer.

PubMed

Thomas, Lynn N; Merrimen, Jennifer; Bell, David G; Rendon, Ricardo; Too, Catherine K L

2015-11-01

Carboxypeptidase-D (CPD) cleaves C-terminal arginine for conversion to nitric oxide (NO) by nitric oxide synthase (NOS). Prolactin (PRL) and androgens stimulate CPD gene transcription and expression, which increases intracellular production of NO to promote viability of prostate cancer (PCa) cells in vitro. The current study evaluated whether hormonal upregulation of CPD and NO promote PCa cell viabilty in vivo, by correlating changes in expression of CPD and nitrotyrosine residues (products of NO action) with proliferation marker Ki67 and associated proteins during PCa development and progression. Fresh prostate tissues, obtained from 40 men with benign prostatic hyperplasia (BPH) or PCa, were flash-frozen at the time of surgery and used for RT-qPCR analysis of CPD, androgen receptor (AR), PRL receptor (PRLR), eNOS, and Ki67 levels. Archival paraffin-embedded tissues from 113 men with BPH or PCa were used for immunohistochemical (IHC) analysis of CPD, nitrotyrosines, phospho-Stat5 (for activated PRLR), AR, eNOS/iNOS, and Ki67. RT-qPCR and IHC analyses showed strong AR and PRLR expression in benign and malignant prostates. CPD mRNA levels increased ∼threefold in PCa compared to BPH, which corresponded to a twofold increase in Ki67 mRNA levels. IHC analysis showed a progressive increase in CPD from 11.4 ± 2.1% in benign to 21.8 ± 3.2% in low-grade (P = 0.007), 40.7 ± 4.0% in high-grade (P < 0.0001) and 50.0 ± 9.5% in castration-recurrent PCa (P < 0.0001). Immunostaining for nitrotyrosines and Ki67 mirrored these increases during PCa progression. CPD, nitrotyrosines, and Ki67 tended to co-localize, as did phospho-Stat5. CPD, nitrotyrosine, and Ki67 levels were higher in PCa than in benign and tended to co-localize, along with phospho-Stat5. The strong correlation in expression of these proteins in benign and malignant prostate tissues, combined with abundant AR and PRLR, supports in vitro evidence that the CPD-Arg-NO pathway is involved in the regulation of PCa cell proliferation. It further highlights a role for PRL in the development and progression of PCa. © 2015 Wiley Periodicals, Inc.

Seasonal rationalization of river water quality sampling locations: a comparative study of the modified Sanders and multivariate statistical approaches.

PubMed

Varekar, Vikas; Karmakar, Subhankar; Jha, Ramakar

2016-02-01

The design of surface water quality sampling location is a crucial decision-making process for rationalization of monitoring network. The quantity, quality, and types of available dataset (watershed characteristics and water quality data) may affect the selection of appropriate design methodology. The modified Sanders approach and multivariate statistical techniques [particularly factor analysis (FA)/principal component analysis (PCA)] are well-accepted and widely used techniques for design of sampling locations. However, their performance may vary significantly with quantity, quality, and types of available dataset. In this paper, an attempt has been made to evaluate performance of these techniques by accounting the effect of seasonal variation, under a situation of limited water quality data but extensive watershed characteristics information, as continuous and consistent river water quality data is usually difficult to obtain, whereas watershed information may be made available through application of geospatial techniques. A case study of Kali River, Western Uttar Pradesh, India, is selected for the analysis. The monitoring was carried out at 16 sampling locations. The discrete and diffuse pollution loads at different sampling sites were estimated and accounted using modified Sanders approach, whereas the monitored physical and chemical water quality parameters were utilized as inputs for FA/PCA. The designed optimum number of sampling locations for monsoon and non-monsoon seasons by modified Sanders approach are eight and seven while that for FA/PCA are eleven and nine, respectively. Less variation in the number and locations of designed sampling sites were obtained by both techniques, which shows stability of results. A geospatial analysis has also been carried out to check the significance of designed sampling location with respect to river basin characteristics and land use of the study area. Both methods are equally efficient; however, modified Sanders approach outperforms FA/PCA when limited water quality and extensive watershed information is available. The available water quality dataset is limited and FA/PCA-based approach fails to identify monitoring locations with higher variation, as these multivariate statistical approaches are data-driven. The priority/hierarchy and number of sampling sites designed by modified Sanders approach are well justified by the land use practices and observed river basin characteristics of the study area.

Detection of compatibility between baclofen and excipients with aid of infrared spectroscopy and chemometry

NASA Astrophysics Data System (ADS)

Rojek, Barbara; Wesolowski, Marek; Suchacz, Bogdan

2013-12-01

In the paper infrared (IR) spectroscopy and multivariate exploration techniques: principal component analysis (PCA) and cluster analysis (CA) were applied as supportive methods for the detection of physicochemical incompatibilities between baclofen and excipients. In the course of research, the most useful rotational strategy in PCA proved to be varimax normalized, while in CA Ward's hierarchical agglomeration with Euclidean distance measure enabled to yield the most interpretable results. Chemometrical calculations confirmed the suitability of PCA and CA as the auxiliary methods for interpretation of infrared spectra in order to recognize whether compatibilities or incompatibilities between active substance and excipients occur. On the basis of IR spectra and the results of PCA and CA it was possible to demonstrate that the presence of lactose, β-cyclodextrin and meglumine in binary mixtures produce interactions with baclofen. The results were verified using differential scanning calorimetry, differential thermal analysis, thermogravimetry/differential thermogravimetry and X-ray powder diffraction analyses.

Free-energy landscape of RNA hairpins constructed via dihedral angle principal component analysis.

PubMed

Riccardi, Laura; Nguyen, Phuong H; Stock, Gerhard

2009-12-31

To systematically construct a low-dimensional free-energy landscape of RNA systems from a classical molecular dynamics simulation, various versions of the principal component analysis (PCA) are compared: the cPCA using the Cartesian coordinates of all atoms, the dPCA using the sine/cosine-transformed six backbone dihedral angles as well as the glycosidic torsional angle chi and the pseudorotational angle P, the aPCA which ignores the circularity of the 6 + 2 dihedral angles of the RNA, and the dPCA(etatheta), which approximates the 6 backbone dihedral angles by 2 pseudotorsional angles eta and theta. As representative examples, a 10-nucleotide UUCG hairpin and the 36-nucleotide segment SL1 of the Psi site of HIV-1 are studied by classical molecular dynamics simulation, using the Amber all-atom force field and explicit solvent. It is shown that the conformational heterogeneity of the RNA hairpins can only be resolved by an angular PCA such as the dPCA but not by the cPCA using Cartesian coordinates. Apart from possible artifacts due to the coupling of overall and internal motion, this is because the details of hydrogen bonding and stacking interactions but also of global structural rearrangements of the RNA are better discriminated by dihedral angles. In line with recent experiments, it is found that the free energy landscape of RNA hairpins is quite rugged and contains various metastable conformational states which may serve as an intermediate for unfolding.

Research on Air Quality Evaluation based on Principal Component Analysis

NASA Astrophysics Data System (ADS)

Wang, Xing; Wang, Zilin; Guo, Min; Chen, Wei; Zhang, Huan

2018-01-01

Economic growth has led to environmental capacity decline and the deterioration of air quality. Air quality evaluation as a fundamental of environmental monitoring and air pollution control has become increasingly important. Based on the principal component analysis (PCA), this paper evaluates the air quality of a large city in Beijing-Tianjin-Hebei Area in recent 10 years and identifies influencing factors, in order to provide reference to air quality management and air pollution control.

Late-onset Alzheimer disease genetic variants in posterior cortical atrophy and posterior AD.

PubMed

Carrasquillo, Minerva M; Khan, Qurat ul Ain; Murray, Melissa E; Krishnan, Siddharth; Aakre, Jeremiah; Pankratz, V Shane; Nguyen, Thuy; Ma, Li; Bisceglio, Gina; Petersen, Ronald C; Younkin, Steven G; Dickson, Dennis W; Boeve, Bradley F; Graff-Radford, Neill R; Ertekin-Taner, Nilüfer

2014-04-22

To investigate association of genetic risk factors for late-onset Alzheimer disease (LOAD) with risk of posterior cortical atrophy (PCA), a syndrome of visual impairment with predominant Alzheimer disease (AD) pathology in posterior cortical regions, and with risk of "posterior AD" neuropathology. We assessed 81 participants with PCA diagnosed clinically and 54 with neuropathologic diagnosis of posterior AD vs 2,523 controls for association with 11 significant single nucleotide polymorphisms (SNPs) from published LOAD risk genome-wide association studies. There was highly significant association with APOE ε4 and increased risk of PCA (p = 0.0003, odds ratio [OR] = 3.17) and posterior AD (p = 1.11 × 10(-17), OR = 6.43). No other locus was significant after corrections for multiple testing, although rs11136000 near CLU (p = 0.019, OR = 0.60) and rs744373 near BIN1 (p = 0.025, OR = 1. 63) associated nominally significantly with posterior AD, and rs3851179 at the PICALM locus had significant association with PCA (p = 0.0003, OR = 2.84). ABCA7 locus SNP rs3764650, which was also tested under the recessive model because of Hardy-Weinberg disequilibrium, also had nominally significant association with PCA risk. The direction of association at APOE, CLU, and BIN1 loci was the same for participants with PCA and posterior AD. The effects for all SNPs, except rs3851179, were consistent with those for LOAD risk. We identified a significant effect for APOE and nominate CLU, BIN1, and ABCA7 as additional risk loci for PCA and posterior AD. Our findings suggest that at least some of the genetic risk factors for LOAD are shared with these atypical conditions and provide effect-size estimates for their future genetic studies.

Red meat and poultry, cooking practices, genetic susceptibility and risk of prostate cancer: results from a multiethnic case–control study

PubMed Central

Stern, Mariana C.

2012-01-01

Red meat, processed and unprocessed, has been considered a potential prostate cancer (PCA) risk factor; epidemiological evidence, however, is inconclusive. An association between meat intake and PCA may be due to potent chemical carcinogens that are generated when meats are cooked at high temperatures. We investigated the association between red meat and poultry intake and localized and advanced PCA taking into account cooking practices and polymorphisms in enzymes that metabolize carcinogens that accumulate in cooked meats. We analyzed data for 1096 controls, 717 localized and 1140 advanced cases from the California Collaborative Prostate Cancer Study, a multiethnic, population-based case–control study. We examined nutrient density-adjusted intake of red meat and poultry and tested for effect modification by 12 SNPs and 2 copy number variants in 10 carcinogen metabolism genes: GSTP1, PTGS2, CYP1A2, CYP2E1, EPHX1, CYP1B1, UGT1A6, NAT2, GSTM1 and GSTT1. We observed a positive association between risk of advanced PCA and high intake of red meat cooked at high temperatures (trend P = 0.026), cooked by pan-frying (trend P = 0.035), and cooked until well-done (trend P = 0.013). An inverse association was observed for baked poultry and advanced PCA risk (trend P = 0.023). A gene-by-diet interaction was observed between an SNP in the PTGS2 gene and the estimated levels of meat mutagens (interaction P = 0.008). Our results support a role for carcinogens that accumulate in meats cooked at high temperatures as potential PCA risk factors, and may support a role for heterocyclic amines (HCAs) in PCA etiology. PMID:22822096

Genetic risk factors for the posterior cortical atrophy variant of Alzheimer's disease.

PubMed

Schott, Jonathan M; Crutch, Sebastian J; Carrasquillo, Minerva M; Uphill, James; Shakespeare, Tim J; Ryan, Natalie S; Yong, Keir X; Lehmann, Manja; Ertekin-Taner, Nilufer; Graff-Radford, Neill R; Boeve, Bradley F; Murray, Melissa E; Khan, Qurat Ul Ain; Petersen, Ronald C; Dickson, Dennis W; Knopman, David S; Rabinovici, Gil D; Miller, Bruce L; González, Aida Suárez; Gil-Néciga, Eulogio; Snowden, Julie S; Harris, Jenny; Pickering-Brown, Stuart M; Louwersheimer, Eva; van der Flier, Wiesje M; Scheltens, Philip; Pijnenburg, Yolande A; Galasko, Douglas; Sarazin, Marie; Dubois, Bruno; Magnin, Eloi; Galimberti, Daniela; Scarpini, Elio; Cappa, Stefano F; Hodges, John R; Halliday, Glenda M; Bartley, Lauren; Carrillo, Maria C; Bras, Jose T; Hardy, John; Rossor, Martin N; Collinge, John; Fox, Nick C; Mead, Simon

2016-08-01

The genetics underlying posterior cortical atrophy (PCA), typically a rare variant of Alzheimer's disease (AD), remain uncertain. We genotyped 302 PCA patients from 11 centers, calculated risk at 24 loci for AD/DLB and performed an exploratory genome-wide association study. We confirm that variation in/near APOE/TOMM40 (P = 6 × 10(-14)) alters PCA risk, but with smaller effect than for typical AD (PCA: odds ratio [OR] = 2.03, typical AD: OR = 2.83, P = .0007). We found evidence for risk in/near CR1 (P = 7 × 10(-4)), ABCA7 (P = .02) and BIN1 (P = .04). ORs at variants near INPP5D and NME8 did not overlap between PCA and typical AD. Exploratory genome-wide association studies confirmed APOE and identified three novel loci: rs76854344 near CNTNAP5 (P = 8 × 10(-10) OR = 1.9 [1.5-2.3]); rs72907046 near FAM46A (P = 1 × 10(-9) OR = 3.2 [2.1-4.9]); and rs2525776 near SEMA3C (P = 1 × 10(-8), OR = 3.3 [2.1-5.1]). We provide evidence for genetic risk factors specifically related to PCA. We identify three candidate loci that, if replicated, may provide insights into selective vulnerability and phenotypic diversity in AD. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Immortalized Cancer-associated Fibroblasts Promote Prostate Cancer Carcinogenesis, Proliferation and Invasion.

PubMed

Yu, Shengqiang; Jiang, Yingjuan; Wan, Fengchun; Wu, Jitao; Gao, Zhenli; Liu, Dongfu

2017-08-01

Cancer-associated fibroblasts (CAFs) are dominant components of the prostate cancer (PCa) stroma. However, the contrasting effects of CAFs and adjacent normal prostate fibroblasts (NPFs) are still poorly defined. The senescence of non-immortalized CAFs after subculture may limit the cell number and influence experimental results of in vitro studies. In this study, we immortalized CAFs to study their role in PCa carcinogenesis, proliferation, and invasion. We cultured and immortalized CAFs and NPFs, then compared their effect on epithelial malignant transformation by using in vitro co-culture, soft agar assay, and a mouse renal capsule xenograft model. We also compared their roles in PCa progression by using in vitro co-culture, cell viability assays, invasion assays, and a mouse xenograft model. For the mechanistic study, we screened a series of growth factors by using real-time polymerase chain reaction. The CAFs and NPFs were successfully cultured, immortalized, and characterized. The CAFs were able to transform prostate epithelial cells into malignant cells, but NPFs were not. The CAFs were more active in promoting proliferation of and invasion by PCa cells, and in secreting higher levels of a series of growth factors. The immortalized CAFs were more supportive of PCa carcinogenesis and progression. Targeting CAFs might be a potential option for PCa therapy. Immortalized CAFs and NPFs will also be valuable resources for future experimental exploration. Copyright© 2017, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

The Health Effects of Masculine Self-Esteem Following Treatment for Localized Prostate Cancer Among Gay Men

PubMed Central

Talcott, James A.; Heeren, Timothy; de Vries, Brian; Blank, Thomas O.; Clark, Jack A.

2016-01-01

Abstract Purpose: To identify factors associated with masculine self-esteem in gay men following treatment for localized prostate cancer (PCa) and to determine the association between masculine self-esteem, PCa-specific factors, and mental health factors in these patients. Methods: A national cross-sectional survey of gay PCa survivors was conducted in 2010–2011. To be eligible for the study, men needed to be age 50 or older, reside in the United States, self-identify as gay, able to read, write, and speak English, and to have been treated for PCa at least 1 year ago. One hundred eleven men returned surveys. Results: After simultaneously adjusting for the factors in our model, men aged 50–64 years and men aged 65–74 years reported lower masculine self-esteem scores than men aged 75 years or older. Lower scores were also reported by men who reported recent severe stigma. Men who reported feeling comfortable revealing their sexual orientation to their doctor reported higher masculine self-esteem scores than men who were not. The mental component score from the SF-12 was also positively correlated with masculine self-esteem. Conclusion: PCa providers are in a position to reduce feelings of stigma and promote resiliency by being aware that they might have gay patients, creating a supportive environment where gay patients can discuss specific sexual concerns, and engaging patients in treatment decisions. These efforts could help not only in reducing stigma but also in increasing masculine self-esteem, thus greatly influencing gay patients' recovery, quality of life, and compliance with follow-up care. PMID:26698658

The Epidemiology of Prostate Cancer in Western Jamaica: Risk Factors, Knowledge, Attitudes and Practices.

PubMed

Dotson, S J; Howard, M D; Aung, M; Keenan, J A; Jolly, P E

2015-05-08

To investigate the epidemiology of prostate cancer (PCa) in western Jamaica and describe the health-seeking behaviour of at-risk men. This study contained both quantitative and qualitative components. The quantitative portion consisted of a retrospective, matched case-control study of two hundred and four men attending outpatient clinics who completed an interviewer-administered questionnaire. The qualitative component consisted of two focus group discussions designed to further investigate health-seeking behaviour and preferred educational channels regarding PCa. Four risk factors were identified: family history of PCa (OR 3.39, 95% CI 1.73, 6.66), age (OR 1.97, 95% CI 1.41, 2.74), any sexually transmitted disease (STD) history (OR 2.02, 95% CI 1.07, 3.83) and alcohol consumption (OR 1.86, 95% CI 1.00, 3.47). Knowledge of primary risk factors was low, especially for race (37%). Although 81% of controls knew tests were available, a stigma was associated with testing. The screening rate was higher than previously reported but still low (56% of controls), and PCa in the western region is discovered by symptoms 61% of the time. Focus group participants blamed a "male mentality" that is antagonistic to routine medical care and preventive testing. Family history, age, STDs and alcohol consumption were identified as risk factors for PCa in western Jamaica. Sexually transmitted disease history and alcohol consumption are interesting results that merit further investigation. Prostate cancer continues to be diagnosed primarily by symptoms, indicating that routine testing is not widespread enough to catch the disease in its early stages when treatment is most effective. A negative image of prostate screenings persists, and targeted educational interventions are needed to improve outcomes.

Protocatechuic aldehyde inhibits migration and proliferation of vascular smooth muscle cells and intravascular thrombosis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Moon, Chang Yoon; Endocrinology, Brain Korea 21 Project for Medical Science, Institute of Endocrine Research, and Severance Integrative Research Institute for Cerebral and Cardiovascular Disease, Yonsei University College of Medicine, Seoul; Ku, Cheol Ryong

2012-06-22

Highlights: Black-Right-Pointing-Pointer Protocatechuic aldehyde (PCA) inhibits ROS production in VSMCs. Black-Right-Pointing-Pointer PCA inhibits proliferation and migration in PDGF-induced VSMCs. Black-Right-Pointing-Pointer PCA has anti-platelet effects in ex vivo rat whole blood. Black-Right-Pointing-Pointer We report the potential therapeutic role of PCA in atherosclerosis. -- Abstract: The migration and proliferation of vascular smooth muscle cells (VSMCs) and formation of intravascular thrombosis play crucial roles in the development of atherosclerotic lesions. This study examined the effects of protocatechuic aldehyde (PCA), a compound isolated from the aqueous extract of the root of Salvia miltiorrhiza, an herb used in traditional Chinese medicine to treat a varietymore » of vascular diseases, on the migration and proliferation of VSMCs and platelets due to platelet-derived growth factor (PDGF). DNA 5-bromo-2 Prime -deoxy-uridine (BrdU) incorporation and wound-healing assays indicated that PCA significantly attenuated PDGF-induced proliferation and migration of VSMCs at a pharmacologically relevant concentration (100 {mu}M). On a molecular level, we observed down-regulation of the phosphatidylinositol 3-kinase (PI3K)/Akt and the mitogen-activated protein kinase (MAPK) pathways, both of which regulate key enzymes associated with migration and proliferation. We also found that PCA induced S-phase arrest of the VSMC cell cycle and suppressed cyclin D2 expression. In addition, PCA inhibited PDGF-BB-stimulated reactive oxygen species production in VSMCs, indicating that PCA's antioxidant properties may contribute to its suppression of PDGF-induced migration and proliferation in VSMCs. Finally, PCA exhibited an anti-thrombotic effect related to its inhibition of platelet aggregation, confirmed with an aggregometer. Together, these findings suggest a potential therapeutic role of PCA in the treatment of atherosclerosis and angioplasty-induced vascular restenosis.« less

Frequency of Propionibacterium acnes Infection in Prostate Glands with Negative Biopsy Results Is an Independent Risk Factor for Prostate Cancer in Patients with Increased Serum PSA Titers.

PubMed

Kakegawa, Tomoya; Bae, Yuan; Ito, Takashi; Uchida, Keisuke; Sekine, Masaki; Nakajima, Yutaka; Furukawa, Asuka; Suzuki, Yoshimi; Kumagai, Jiro; Akashi, Takumi; Eishi, Yoshinobu

2017-01-01

Propionibacterium acnes has recently been implicated as a cause of chronic prostatitis and this commensal bacterium may be linked to prostate carcinogenesis. The occurrence of intracellular P. acnes infection in prostate glands and the higher frequency of P. acnes-positive glands in radical prostatectomy specimens from patients with prostate cancer (PCa) than in those from patients without PCa led us to examine whether the P. acnes-positive gland frequency can be used to assess the risk for PCa in patients whose first prostate biopsy, performed due to an increased prostate-specific antigen (PSA) titer, was negative. We retrospectively collected the first and last prostate biopsy samples from 44 patients that were diagnosed PCa within 4 years after the first negative biopsy and from 36 control patients with no PCa found in repeated biopsy for at least 3 years after the first biopsy. We evaluated P. acnes-positive gland frequency and P. acnes-positive macrophage number using enzyme-immunohistochemistry with a P. acnes-specific monoclonal antibody (PAL antibody). The frequency of P. acnes-positive glands was higher in PCa samples than in control samples in both first biopsy samples and in combined first and last biopsy samples (P < 0.001). A frequency greater than the threshold (18.5 and 17.7, respectively) obtained by each receiver operating characteristic curve was an independent risk factor for PCa (P = 0.003 and 0.001, respectively) with odds ratios (14.8 and 13.9, respectively) higher than those of serum PSA titers of patients just before each biopsy (4.6 and 2.3, respectively). The number of P. acnes-positive macrophages did not differ significantly between PCa and control samples. These results suggested that the frequency of P. acnes-positive glands in the first negative prostate biopsy performed due to increased PSA titers can be supportive information for urologists in planning repeated biopsy or follow-up strategies.

A 17-gene assay to predict prostate cancer aggressiveness in the context of Gleason grade heterogeneity, tumor multifocality, and biopsy undersampling.

PubMed

Klein, Eric A; Cooperberg, Matthew R; Magi-Galluzzi, Cristina; Simko, Jeffry P; Falzarano, Sara M; Maddala, Tara; Chan, June M; Li, Jianbo; Cowan, Janet E; Tsiatis, Athanasios C; Cherbavaz, Diana B; Pelham, Robert J; Tenggara-Hunter, Imelda; Baehner, Frederick L; Knezevic, Dejan; Febbo, Phillip G; Shak, Steven; Kattan, Michael W; Lee, Mark; Carroll, Peter R

2014-09-01

Prostate tumor heterogeneity and biopsy undersampling pose challenges to accurate, individualized risk assessment for men with localized disease. To identify and validate a biopsy-based gene expression signature that predicts clinical recurrence, prostate cancer (PCa) death, and adverse pathology. Gene expression was quantified by reverse transcription-polymerase chain reaction for three studies-a discovery prostatectomy study (n=441), a biopsy study (n=167), and a prospectively designed, independent clinical validation study (n=395)-testing retrospectively collected needle biopsies from contemporary (1997-2011) patients with low to intermediate clinical risk who were candidates for active surveillance (AS). The main outcome measures defining aggressive PCa were clinical recurrence, PCa death, and adverse pathology at prostatectomy. Cox proportional hazards regression models were used to evaluate the association between gene expression and time to event end points. Results from the prostatectomy and biopsy studies were used to develop and lock a multigene-expression-based signature, called the Genomic Prostate Score (GPS); in the validation study, logistic regression was used to test the association between the GPS and pathologic stage and grade at prostatectomy. Decision-curve analysis and risk profiles were used together with clinical and pathologic characteristics to evaluate clinical utility. Of the 732 candidate genes analyzed, 288 (39%) were found to predict clinical recurrence despite heterogeneity and multifocality, and 198 (27%) were predictive of aggressive disease after adjustment for prostate-specific antigen, Gleason score, and clinical stage. Further analysis identified 17 genes representing multiple biological pathways that were combined into the GPS algorithm. In the validation study, GPS predicted high-grade (odds ratio [OR] per 20 GPS units: 2.3; 95% confidence interval [CI], 1.5-3.7; p<0.001) and high-stage (OR per 20 GPS units: 1.9; 95% CI, 1.3-3.0; p=0.003) at surgical pathology. GPS predicted high-grade and/or high-stage disease after controlling for established clinical factors (p<0.005) such as an OR of 2.1 (95% CI, 1.4-3.2) when adjusting for Cancer of the Prostate Risk Assessment score. A limitation of the validation study was the inclusion of men with low-volume intermediate-risk PCa (Gleason score 3+4), for whom some providers would not consider AS. Genes representing multiple biological pathways discriminate PCa aggressiveness in biopsy tissue despite tumor heterogeneity, multifocality, and limited sampling at time of biopsy. The biopsy-based 17-gene GPS improves prediction of the presence or absence of adverse pathology and may help men with PCa make more informed decisions between AS and immediate treatment. Prostate cancer (PCa) is often present in multiple locations within the prostate and has variable characteristics. We identified genes with expression associated with aggressive PCa to develop a biopsy-based, multigene signature, the Genomic Prostate Score (GPS). GPS was validated for its ability to predict men who have high-grade or high-stage PCa at diagnosis and may help men diagnosed with PCa decide between active surveillance and immediate definitive treatment. Copyright © 2014 European Association of Urology. Published by Elsevier B.V. All rights reserved.

Circular RNA Myosin Light Chain Kinase (MYLK) Promotes Prostate Cancer Progression through Modulating Mir-29a Expression.

PubMed

Dai, Yuanqing; Li, Dongjie; Chen, Xiong; Tan, Xinji; Gu, Jie; Chen, Mingquan; Zhang, Xiaobo

2018-05-25

BACKGROUND In developed countries, prostate cancer (PCa) is a frequently diagnosed cancer with the second highest fatality rate. Circular RNAs (circRNAs) are a class of endogenous non-coding RNAs (ncRNAs) stably expressed in cells and involved in a series of carcinomas. However, few research studies have reported on the role of circRNAs in PCa. MATERIAL AND METHODS We used qRT-PCR to detect the expression of circMYLK (circRNA ID: hsa_circ_0141940) and miR-29a in PCa tissues and cell lines. MTT, colony formation, and TUNEL assays were performed to analysis the cell viability of PCa cells. Transwell and wound scratch assays were performed to investigate the cell invasion and migration of PCa cells. RESULTS In the present study, we confirmed that circMYLK expression level was significantly higher in PCa samples and PCa cells than in normal tissues and normal prostatic cells. The upregulated circRNA-MYLK promoted PCa cells proliferation, invasion, and migration; however, si-circRNA-MYLK significantly accelerated the PCa cell apoptosis. We also observed that the aforementioned function of circRNA-MYLK on PCa cells was affected through targeting miR-29a. CONCLUSIONS We confirmed circRNA-MYLK was an oncogene in PCa and revealed a novel mechanism underlying circRNA-MYLK in PC progression.

The theoretical and experimental study on dicalcium phosphate dehydrate loading with protocatechuic aldehyde.

PubMed

Guo, Yuehua; Qu, Shuxin; Lu, Xiong; Xie, Haodong; Zhang, Hongping; Weng, Jie

2010-07-01

The aim of this study is to investigate the interaction between dicalcium phosphate dihydrate (CaHPO(4) x 2H(2)O, DCPD) and Protocatechuic aldehyde (C(7)H(6)O(3), Pca), which is the water-soluble constituents of Chinese Medicine, Salvia Miltiorrhiza Bunge (SMB), by calculating the absorption energy through molecular dynamics simulation. Furthermore, the effects of functional groups of Pca and temperature on Pca adsorbed by DCPD are calculated respectively. DCPD/Pca and DCPD were analyzed by X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR) and thermogravimetric analysis (TG). The simulation results showed that Pca mostly absorbed on the (0 2 0) surface of DCPD. The aldehyde group of Pca played a moren important role on the adsorption of Pca on DCPD than hydroxyl did, while temperature had no distinct effects on the adsorption. XRD results indicated that Pca induced the preferential growth of (0 2 0) crystal surface in DCPC/Pca whereas it had no influence on the crystal structure, the crystallinity and grain size of DCPD. FTIR and TG results showed that the characteristic peak of Pca was at 1295 cm(-1) and the content of Pca in DCPD was 16%, respectively. The present results show that molecular dynamics simulation is a very effective and complementary method to study the interaction between materials and medicine.

Cyanidin-3-glucoside and its phenolic acid metabolites attenuate visible light-induced retinal degeneration in vivo via activation of Nrf2/HO-1 pathway and NF-κB suppression.

PubMed

Wang, Yong; Huo, Yazhen; Zhao, Liang; Lu, Feng; Wang, Ou; Yang, Xue; Ji, Baoping; Zhou, Feng

2016-07-01

Cyanidin-3-glucoside (C3G) is a major anthocyanin in berries and a potential nutritional supplement for preventing retinal degeneration. However, the protective mechanism of C3G and its metabolites, protocatechuic acid (PCA) and ferulic acid (FA), remain unclear. The molecular mechanisms of C3G and its metabolites against retinal photooxidative damage in vivo are investigated. Pigmented rabbits were orally administered C3G, PCA, and FA (0.11 mmol/kg/day) for 3 weeks. Electroretinography, histological analysis, and TUNEL assay showed that C3G and its metabolites attenuated retinal cell apoptosis. The expression of oxidative stress markers were upregulated after light exposure but attenuated by C3G and FA, which may be attributed to the elevated secretion and expression of heme oxygenase (HO-1) and nuclear factor erythroid-2 related factor 2 (Nrf2). C3G, PCA, and FA attenuated the secretion or expression of inflammation-related genes; FA suppressed nuclear factor kappa B (NF-κB) activation. The treatments attenuated the light-induced changes on certain apoptotic proteins and angiogenesis-related cytokines. C3G and FA reduced light-induced retinal oxidative stress by activating the Nrf2/HO-1 antioxidant pathway. FA attenuated the light-induced retinal inflammation by suppressing NF-κB activation. C3G and its metabolites attenuated the photooxidation-induced apoptosis and angiogenesis in the retina. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Characterizing the molecular features of ERG-positive tumors in primary and castration resistant prostate cancer.

PubMed

Roudier, Martine P; Winters, Brian R; Coleman, Ilsa; Lam, Hung-Ming; Zhang, Xiaotun; Coleman, Roger; Chéry, Lisly; True, Lawrence D; Higano, Celestia S; Montgomery, Bruce; Lange, Paul H; Snyder, Linda A; Srivastava, Shiv; Corey, Eva; Vessella, Robert L; Nelson, Peter S; Üren, Aykut; Morrissey, Colm

2016-06-01

The TMPRSS2-ERG gene fusion is detected in approximately half of primary prostate cancers (PCa) yet the prognostic significance remains unclear. We hypothesized that ERG promotes the expression of common genes in primary PCa and metastatic castration-resistant PCa (CRPC), with the objective of identifying ERG-associated pathways, which may promote the transition from primary PCa to CRPC. We constructed tissue microarrays (TMA) from 127 radical prostatectomy specimens, 20 LuCaP patient-derived xenografts (PDX), and 152 CRPC metastases obtained immediately at time of death. Nuclear ERG was assessed by immunohistochemistry (IHC). To characterize the molecular features of ERG-expressing PCa, a subset of IHC confirmed ERG+ or ERG- specimens including 11 radical prostatectomies, 20 LuCaP PDXs, and 45 CRPC metastases underwent gene expression analysis. Genes were ranked based on expression in primary PCa and CRPC. Common genes of interest were targeted for IHC analysis and expression compared with biochemical recurrence (BCR) status. IHC revealed that 43% of primary PCa, 35% of the LuCaP PDXs, and 18% of the CRPC metastases were ERG+ (12 of 48 patients [25%] had at least one ERG+ metastasis). Based on gene expression data and previous literature, two proteins involved in calcium signaling (NCALD, CACNA1D), a protein involved in inflammation (HLA-DMB), CD3 positive immune cells, and a novel ERG-associated protein, DCLK1 were evaluated in primary PCa and CRPC metastases. In ERG+ primary PCa, a weak association was seen with NCALD and CACNA1D protein expression. HLA-DMB association with ERG was decreased and CD3 cell number association with ERG was changed from positive to negative in CRPC metastases compared to primary PCa. DCLK1 was upregulated at the protein level in unpaired ERG+ primary PCa and CRPC metastases (P = 0.0013 and P < 0.0001, respectively). In primary PCa, ERG status or expression of targeted proteins was not associated with BCR-free survival. However, for primary PCa, ERG+DCLK1+ patients exhibited shorter time to BCR (P = 0.06) compared with ERG+DCLK1- patients. This study examined ERG expression in primary PCa and CRPC. We have identified altered levels of inflammatory mediators associated with ERG expression. We determined expression of DCLK1 correlates with ERG expression and may play a role in primary PCa progression to metastatic CPRC. Prostate 76:810-822, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

A two-stage linear discriminant analysis via QR-decomposition.

PubMed

Ye, Jieping; Li, Qi

2005-06-01

Linear Discriminant Analysis (LDA) is a well-known method for feature extraction and dimension reduction. It has been used widely in many applications involving high-dimensional data, such as image and text classification. An intrinsic limitation of classical LDA is the so-called singularity problems; that is, it fails when all scatter matrices are singular. Many LDA extensions were proposed in the past to overcome the singularity problems. Among these extensions, PCA+LDA, a two-stage method, received relatively more attention. In PCA+LDA, the LDA stage is preceded by an intermediate dimension reduction stage using Principal Component Analysis (PCA). Most previous LDA extensions are computationally expensive, and not scalable, due to the use of Singular Value Decomposition or Generalized Singular Value Decomposition. In this paper, we propose a two-stage LDA method, namely LDA/QR, which aims to overcome the singularity problems of classical LDA, while achieving efficiency and scalability simultaneously. The key difference between LDA/QR and PCA+LDA lies in the first stage, where LDA/QR applies QR decomposition to a small matrix involving the class centroids, while PCA+LDA applies PCA to the total scatter matrix involving all training data points. We further justify the proposed algorithm by showing the relationship among LDA/QR and previous LDA methods. Extensive experiments on face images and text documents are presented to show the effectiveness of the proposed algorithm.

Functional Data Analysis in NTCP Modeling: A New Method to Explore the Radiation Dose-Volume Effects

DOE Office of Scientific and Technical Information (OSTI.GOV)

Benadjaoud, Mohamed Amine, E-mail: mohamedamine.benadjaoud@gustaveroussy.fr; Université Paris sud, Le Kremlin-Bicêtre; Institut Gustave Roussy, Villejuif

2014-11-01

Purpose/Objective(s): To describe a novel method to explore radiation dose-volume effects. Functional data analysis is used to investigate the information contained in differential dose-volume histograms. The method is applied to the normal tissue complication probability modeling of rectal bleeding (RB) for patients irradiated in the prostatic bed by 3-dimensional conformal radiation therapy. Methods and Materials: Kernel density estimation was used to estimate the individual probability density functions from each of the 141 rectum differential dose-volume histograms. Functional principal component analysis was performed on the estimated probability density functions to explore the variation modes in the dose distribution. The functional principalmore » components were then tested for association with RB using logistic regression adapted to functional covariates (FLR). For comparison, 3 other normal tissue complication probability models were considered: the Lyman-Kutcher-Burman model, logistic model based on standard dosimetric parameters (LM), and logistic model based on multivariate principal component analysis (PCA). Results: The incidence rate of grade ≥2 RB was 14%. V{sub 65Gy} was the most predictive factor for the LM (P=.058). The best fit for the Lyman-Kutcher-Burman model was obtained with n=0.12, m = 0.17, and TD50 = 72.6 Gy. In PCA and FLR, the components that describe the interdependence between the relative volumes exposed at intermediate and high doses were the most correlated to the complication. The FLR parameter function leads to a better understanding of the volume effect by including the treatment specificity in the delivered mechanistic information. For RB grade ≥2, patients with advanced age are significantly at risk (odds ratio, 1.123; 95% confidence interval, 1.03-1.22), and the fits of the LM, PCA, and functional principal component analysis models are significantly improved by including this clinical factor. Conclusion: Functional data analysis provides an attractive method for flexibly estimating the dose-volume effect for normal tissues in external radiation therapy.« less

A comprehensive evaluation of CHEK2 germline mutations in men with prostate cancer.

PubMed

Wu, Yishuo; Yu, Hongjie; Zheng, S Lilly; Na, Rong; Mamawala, Mufaddal; Landis, Tricia; Wiley, Kathleen; Petkewicz, Jacqueline; Shah, Sameep; Shi, Zhuqing; Novakovic, Kristian; McGuire, Michael; Brendler, Charles B; Ding, Qiang; Helfand, Brian T; Carter, H Ballentine; Cooney, Kathleen A; Isaacs, William B; Xu, Jianfeng

2018-06-01

Germline mutations in CHEK2 have been associated with prostate cancer (PCa) risk. Our objective is to examine whether germline pathogenic CHEK2 mutations can differentiate risk of lethal from indolent PCa. A case-case study of 703 lethal PCa patients and 1455 patients with low-risk localized PCa of European, African, and Chinese origin was performed. Germline DNA samples from these patients were sequenced for CHEK2. Mutation carrier rates and their association with lethal PCa were analyzed using the Fisher exact test and Kaplan-Meier survival analysis. In the entire study population, 40 (1.85%) patients were identified as carrying one of 15 different germline CHEK2 pathogenic or likely pathogenic mutations. CHEK2 mutations were detected in 16 (2.28%) of 703 lethal PCa patients compared with 24 (1.65%) of 1455 low-risk PCa patients (P = 0.31). No association was found between CHEK2 mutation status and early-diagnosis or PCa-specific survival time. However, the most common mutation in CHEK2, c.1100delC (p.T367 fs), had a significantly higher carrier rate (1.28%) in lethal PCa patients than low-risk PCa patients of European American origin (0.16%), P = 0.0038. The estimated Odds Ratio of this mutation for lethal PCa was 7.86. The carrier rate in lethal PCa was also significantly higher than that (0.46%) in 32 461 non-Finnish European subjects from the Exome Aggregation Consortium (ExAC) (P = 0.01). While overall CHEK2 mutations were not significantly more common in men with lethal compared to low-risk PCa, the specific CHEK2 mutation, c.1100delC, appears to contribute to an increased risk of lethal PCa in European American men. © 2018 Wiley Periodicals, Inc.

Sparse principal component analysis in medical shape modeling

NASA Astrophysics Data System (ADS)

Sjöstrand, Karl; Stegmann, Mikkel B.; Larsen, Rasmus

2006-03-01

Principal component analysis (PCA) is a widely used tool in medical image analysis for data reduction, model building, and data understanding and exploration. While PCA is a holistic approach where each new variable is a linear combination of all original variables, sparse PCA (SPCA) aims at producing easily interpreted models through sparse loadings, i.e. each new variable is a linear combination of a subset of the original variables. One of the aims of using SPCA is the possible separation of the results into isolated and easily identifiable effects. This article introduces SPCA for shape analysis in medicine. Results for three different data sets are given in relation to standard PCA and sparse PCA by simple thresholding of small loadings. Focus is on a recent algorithm for computing sparse principal components, but a review of other approaches is supplied as well. The SPCA algorithm has been implemented using Matlab and is available for download. The general behavior of the algorithm is investigated, and strengths and weaknesses are discussed. The original report on the SPCA algorithm argues that the ordering of modes is not an issue. We disagree on this point and propose several approaches to establish sensible orderings. A method that orders modes by decreasing variance and maximizes the sum of variances for all modes is presented and investigated in detail.

A new statistical PCA-ICA algorithm for location of R-peaks in ECG.

PubMed

Chawla, M P S; Verma, H K; Kumar, Vinod

2008-09-16

The success of ICA to separate the independent components from the mixture depends on the properties of the electrocardiogram (ECG) recordings. This paper discusses some of the conditions of independent component analysis (ICA) that could affect the reliability of the separation and evaluation of issues related to the properties of the signals and number of sources. Principal component analysis (PCA) scatter plots are plotted to indicate the diagnostic features in the presence and absence of base-line wander in interpreting the ECG signals. In this analysis, a newly developed statistical algorithm by authors, based on the use of combined PCA-ICA for two correlated channels of 12-channel ECG data is proposed. ICA technique has been successfully implemented in identifying and removal of noise and artifacts from ECG signals. Cleaned ECG signals are obtained using statistical measures like kurtosis and variance of variance after ICA processing. This analysis also paper deals with the detection of QRS complexes in electrocardiograms using combined PCA-ICA algorithm. The efficacy of the combined PCA-ICA algorithm lies in the fact that the location of the R-peaks is bounded from above and below by the location of the cross-over points, hence none of the peaks are ignored or missed.

Finding Imaging Patterns of Structural Covariance via Non-Negative Matrix Factorization

PubMed Central

Sotiras, Aristeidis; Resnick, Susan M.; Davatzikos, Christos

2015-01-01

In this paper, we investigate the use of Non-Negative Matrix Factorization (NNMF) for the analysis of structural neuroimaging data. The goal is to identify the brain regions that co-vary across individuals in a consistent way, hence potentially being part of underlying brain networks or otherwise influenced by underlying common mechanisms such as genetics and pathologies. NNMF offers a directly data-driven way of extracting relatively localized co-varying structural regions, thereby transcending limitations of Principal Component Analysis (PCA), Independent Component Analysis (ICA) and other related methods that tend to produce dispersed components of positive and negative loadings. In particular, leveraging upon the well known ability of NNMF to produce parts-based representations of image data, we derive decompositions that partition the brain into regions that vary in consistent ways across individuals. Importantly, these decompositions achieve dimensionality reduction via highly interpretable ways and generalize well to new data as shown via split-sample experiments. We empirically validate NNMF in two data sets: i) a Diffusion Tensor (DT) mouse brain development study, and ii) a structural Magnetic Resonance (sMR) study of human brain aging. We demonstrate the ability of NNMF to produce sparse parts-based representations of the data at various resolutions. These representations seem to follow what we know about the underlying functional organization of the brain and also capture some pathological processes. Moreover, we show that these low dimensional representations favorably compare to descriptions obtained with more commonly used matrix factorization methods like PCA and ICA. PMID:25497684

Variants on 8q24 and prostate cancer risk in Chinese population: a meta-analysis.

PubMed

Ren, Xiao-Qiang; Zhang, Jian-Guo; Xin, Shi-Yong; Cheng, Tao; Li, Liang; Ren, Wei-Hua

2015-01-01

Previous studies have identified 8q24 as an important region to prostate cancer (PCa) susceptibility. The aim of this study was to investigate the role of six genetic variants on 8q24 (rs1447295, A; rs6983267, G; rs6983561, C; rs7837688, T; rs10090154, T and rs16901979, A) on PCa risk in Chinese population. Online electronic databases were searched to retrieve related articles concerning the association between 8q24 variants and PCa risk in men of Chinese population published between 2000 and 2014. Odds ratio (ORs) with its 95% correspondence interval (CI) were employed to assess the strength of association. Total eleven case-control studies were screened out, including 2624 PCa patients and 2438 healthy controls. Our results showed that three risk alleles of rs1447295 A (OR=1.35, 95% CI=1.19-1.53, P<0.00001), rs6983561 C (C vs. A: OR=1.41, 95% CI=1.21-1.63, P<0.00001) and rs10090154 T (T vs. C: OR=1.48, 95% CI=1.22-1.80, P<0.00001) on8q24 were significantly associated with PCa risk in Chinese population. Furthermore, genotypes of rs1447295, AA+AC; rs6983561, CC+AC and CC; rs10090154, TT+TC; and rs16901979, AA were associated with PCa as well (P<0.01). No association was found between rs6983267, rs7837688 and PCa risk. In conclusions, variants including rs1447295, rs6983561, rs10090154 and rs16901979 on 8q24 might be associated with PCa risk in Chinese population, indicating these four variations may contribute risk to this disease. This meta-analysis was the first study to assess the role of 8q24 variants on PCa risk in Chinese population.

An Estimate of the Incidence of Prostate Cancer in Africa: A Systematic Review and Meta-Analysis

PubMed Central

Aderemi, Adewale Victor; Iseolorunkanmi, Alexander; Oyedokun, Ayo; Ayo, Charles K.

2016-01-01

Background Prostate cancer (PCa) is rated the second most common cancer and sixth leading cause of cancer deaths among men globally. Reports show that African men suffer disproportionately from PCa compared to men from other parts of the world. It is still quite difficult to accurately describe the burden of PCa in Africa due to poor cancer registration systems. We systematically reviewed the literature on prostate cancer in Africa and provided a continent-wide incidence rate of PCa based on available data in the region. Methods A systematic literature search of Medline, EMBASE and Global Health from January 1980 to June 2015 was conducted, with additional search of Google Scholar, International Association of Cancer Registries (IACR), International Agency for Research on Cancer (IARC), and WHO African region websites, for studies that estimated incidence rate of PCa in any African location. Having assessed quality and consistency across selected studies, we extracted incidence rates of PCa and conducted a random effects meta-analysis. Results Our search returned 9766 records, with 40 studies spreading across 16 African countries meeting our selection criteria. We estimated a pooled PCa incidence rate of 22.0 (95% CI: 19.93–23.97) per 100,000 population, and also reported a median incidence rate of 19.5 per 100,000 population. We observed an increasing trend in PCa incidence with advancing age, and over the main years covered. Conclusion Effective cancer registration and extensive research are vital to appropriately quantifying PCa burden in Africa. We hope our findings may further assist at identifying relevant gaps, and contribute to improving knowledge, research, and interventions targeted at prostate cancer in Africa. PMID:27073921

Decision tree and PCA-based fault diagnosis of rotating machinery

NASA Astrophysics Data System (ADS)

Sun, Weixiang; Chen, Jin; Li, Jiaqing

2007-04-01

After analysing the flaws of conventional fault diagnosis methods, data mining technology is introduced to fault diagnosis field, and a new method based on C4.5 decision tree and principal component analysis (PCA) is proposed. In this method, PCA is used to reduce features after data collection, preprocessing and feature extraction. Then, C4.5 is trained by using the samples to generate a decision tree model with diagnosis knowledge. At last the tree model is used to make diagnosis analysis. To validate the method proposed, six kinds of running states (normal or without any defect, unbalance, rotor radial rub, oil whirl, shaft crack and a simultaneous state of unbalance and radial rub), are simulated on Bently Rotor Kit RK4 to test C4.5 and PCA-based method and back-propagation neural network (BPNN). The result shows that C4.5 and PCA-based diagnosis method has higher accuracy and needs less training time than BPNN.

On a PCA-based lung motion model

NASA Astrophysics Data System (ADS)

Li, Ruijiang; Lewis, John H.; Jia, Xun; Zhao, Tianyu; Liu, Weifeng; Wuenschel, Sara; Lamb, James; Yang, Deshan; Low, Daniel A.; Jiang, Steve B.

2011-09-01

Respiration-induced organ motion is one of the major uncertainties in lung cancer radiotherapy and is crucial to be able to accurately model the lung motion. Most work so far has focused on the study of the motion of a single point (usually the tumor center of mass), and much less work has been done to model the motion of the entire lung. Inspired by the work of Zhang et al (2007 Med. Phys. 34 4772-81), we believe that the spatiotemporal relationship of the entire lung motion can be accurately modeled based on principle component analysis (PCA) and then a sparse subset of the entire lung, such as an implanted marker, can be used to drive the motion of the entire lung (including the tumor). The goal of this work is twofold. First, we aim to understand the underlying reason why PCA is effective for modeling lung motion and find the optimal number of PCA coefficients for accurate lung motion modeling. We attempt to address the above important problems both in a theoretical framework and in the context of real clinical data. Second, we propose a new method to derive the entire lung motion using a single internal marker based on the PCA model. The main results of this work are as follows. We derived an important property which reveals the implicit regularization imposed by the PCA model. We then studied the model using two mathematical respiratory phantoms and 11 clinical 4DCT scans for eight lung cancer patients. For the mathematical phantoms with cosine and an even power (2n) of cosine motion, we proved that 2 and 2n PCA coefficients and eigenvectors will completely represent the lung motion, respectively. Moreover, for the cosine phantom, we derived the equivalence conditions for the PCA motion model and the physiological 5D lung motion model (Low et al 2005 Int. J. Radiat. Oncol. Biol. Phys. 63 921-9). For the clinical 4DCT data, we demonstrated the modeling power and generalization performance of the PCA model. The average 3D modeling error using PCA was within 1 mm (0.7 ± 0.1 mm). When a single artificial internal marker was used to derive the lung motion, the average 3D error was found to be within 2 mm (1.8 ± 0.3 mm) through comprehensive statistical analysis. The optimal number of PCA coefficients needs to be determined on a patient-by-patient basis and two PCA coefficients seem to be sufficient for accurate modeling of the lung motion for most patients. In conclusion, we have presented thorough theoretical analysis and clinical validation of the PCA lung motion model. The feasibility of deriving the entire lung motion using a single marker has also been demonstrated on clinical data using a simulation approach.

Differences in chewing sounds of dry-crisp snacks by multivariate data analysis

NASA Astrophysics Data System (ADS)

De Belie, N.; Sivertsvik, M.; De Baerdemaeker, J.

2003-09-01

Chewing sounds of different types of dry-crisp snacks (two types of potato chips, prawn crackers, cornflakes and low calorie snacks from extruded starch) were analysed to assess differences in sound emission patterns. The emitted sounds were recorded by a microphone placed over the ear canal. The first bite and the first subsequent chew were selected from the time signal and a fast Fourier transformation provided the power spectra. Different multivariate analysis techniques were used for classification of the snack groups. This included principal component analysis (PCA) and unfold partial least-squares (PLS) algorithms, as well as multi-way techniques such as three-way PLS, three-way PCA (Tucker3), and parallel factor analysis (PARAFAC) on the first bite and subsequent chew. The models were evaluated by calculating the classification errors and the root mean square error of prediction (RMSEP) for independent validation sets. It appeared that the logarithm of the power spectra obtained from the chewing sounds could be used successfully to distinguish the different snack groups. When different chewers were used, recalibration of the models was necessary. Multi-way models distinguished better between chewing sounds of different snack groups than PCA on bite or chew separately and than unfold PLS. From all three-way models applied, N-PLS with three components showed the best classification capabilities, resulting in classification errors of 14-18%. The major amount of incorrect classifications was due to one type of potato chips that had a very irregular shape, resulting in a wide variation of the emitted sounds.

The influence of stigma on the quality of life for prostate cancer survivors.

PubMed

Wood, Andrew W; Barden, Sejal; Terk, Mitchell; Cesaretti, Jamie

2017-01-01

The purpose of the present study was to investigate the influence of stigma on prostate cancer (PCa) survivors' quality of life. Stigma for lung cancer survivors has been the focus of considerable research (Else-Quest & Jackson, 2014); however, gaps remain in understanding the experience of PCa stigma. A cross-sectional correlational study was designed to assess the incidence of PCa stigma and its influence on the quality of life of survivors. Eighty-five PCa survivors were administered survey packets consisting of a stigma measure, a PCa-specific quality of life measure, and a demographic survey during treatment of their disease. A linear regression analysis was conducted with the data received from PCa survivors. Results indicated that PCa stigma has a significant, negative influence on the quality of life for survivors (R 2 = 0.33, F(4, 80) = 11.53, p < 0.001). There were no statistically significant differences in PCa stigma based on demographic variables (e.g., race and age). Implications for physical and mental health practitioners and researchers are discussed.

Mutational Landscape of Candidate Genes in Familial Prostate Cancer

PubMed Central

Johnson, Anna M.; Zuhlke, Kimberly A.; Plotts, Chris; McDonnell, Shannon K.; Middha, Sumit; Riska, Shaun M.; Thibodeau, Stephen N.; Douglas, Julie A.; Cooney, Kathleen A.

2014-01-01

Background Family history is a major risk factor for prostate cancer (PCa), suggesting a genetic component to the disease. However, traditional linkage and association studies have failed to fully elucidate the underlying genetic basis of familial PCa. Methods Here we use a candidate gene approach to identify potential PCa susceptibility variants in whole exome sequencing data from familial PCa cases. Six hundred ninety-seven candidate genes were identified based on function, location near a known chromosome 17 linkage signal, and/or previous association with prostate or other cancers. Single nucleotide variants (SNVs) in these candidate genes were identified in whole exome sequence data from 33 PCa cases from 11 multiplex PCa families (3 cases/family). Results Overall, 4856 candidate gene SNVs were identified, including 1052 missense and 10 nonsense variants. Twenty missense variants were shared by all 3 family members in each family in which they were observed. Additionally, 15 missense variants were shared by 2 of 3 family members and predicted to be deleterious by 5 different algorithms. Four missense variants, BLM Gln123Arg, PARP2 Arg283Gln, LRCC46 Ala295Thr and KIF2B Pro91Leu, and 1 nonsense variant, CYP3A43 Arg441Ter, showed complete co-segregation with PCa status. Twelve additional variants displayed partial co-segregation with PCa. Conclusions Forty-three nonsense and shared, missense variants were identified in our candidate genes. Further research is needed to determine the contribution of these variants to PCa susceptibility. PMID:25111073

[Development, factor-analytical control and psychometric evaluation of a questionnaire on specialty choices among medical students].

PubMed

Hermann, K; Buchholz, A; Loh, A; Kiolbassa, K; Miksch, A; Joos, S; Götz, K

2012-07-01

A questionnaire was developed and validated which assesses factors influencing career choices of medical students and their perception of possibilities in general practice. The first questionnaire version, which was developed based on a systematic literature review, was checked for comprehensibility and redundancy using concurrent think aloud. The revised version was filled out by a pilot sample of medical students and the factor structure was assessed using principal component analysis (PCA). The final version was filled out in an online survey by medical students of all 5 Medical Faculties in the federal state of Baden-Wuerttemberg. The factor structure was validated with a confirmatory factor analysis (CFA). Reliability was assessed as internal consistency using Cronbach's α. The questionnaire comprises 2 parts: ratings of (A) the individual importance and of (B) the possibilities in general practice on 5-point scales. The first version comprising 118 items was shortened to 63 items after conducting interviews using concurrent think aloud. A further 3 items giving no information were removed after piloting the questionnaire on 179 students. The 27 items of part A were structured in 7 factors (PCA): image, personal ambition, patient orientation, work-life balance, future perspectives, job-related ambition, and variety in job. This structure had a critical fit in the CFA applied to the final version filled out by 1 299 students. Internal consistency of the factors was satisfactory to very good (Cronbach's α=0.55-0.81). The questionnaire showed good psychometric properties. Further, not assessed factors influence career choice resulting in unexplained variance in our dataset and the critical fit of the model. © Georg Thieme Verlag KG Stuttgart · New York.

Evaluation of Vitronectin Expression in Prostate Cancer and the Clinical Significance of the Association of Vitronectin Expression with Prostate Specific Antigen in Detecting Prostate Cancer.

PubMed

Niu, Yue; Zhang, Ling; Bi, Xing; Yuan, Shuai; Chen, Peng

2016-03-05

To detect the expression of vitronectin (VTN) in the tissues and blood serum of prostate cancer (PCa) patients, and evaluate its clinical significance and to evaluate the significance of the combined assay of VTN and prostate specific antigens (PSA) in PCa diagnosis. To detect the expression of VTN as a potential marker for PCa diagnosis and prognosis, immunohistochemistry was performed on the tissues of 32 patients with metastatic PCa (PCaM), 34 patients with PCa without metastasis (PCa), and 41 patients with benign prostatic hyperplasia (BPH). The sera were then subjected to Western blot analysis. All cases were subsequently examined to determine the concentrations of PSA and VTN in the sera. The collected data were collated and analyzed. The positive expression rates of VTN in the tissues of the BPH and PCa groups (including PCa and PCaM groups) were 75.61% and 45.45%, respectively (P = .005). VTN was more highly expressed in the sera of the BPH patients (0.83 ± 0.07) than in the sera of the PCa patients (0.65 ± 0.06) (P < .05). It was also more highly expressed in the sera of the PCa patients than in the sera of the PCaM patients (0.35 ± 0.08) (P < .05). In the diagnosis of BPH and PCa, the Youden indexes of PSA detection, VTN detection, and combined detection were 0.2620, 0.3468, and 0.5635; the kappa values were 0.338, 0.304, and 0.448, respectively, and the areas under the receiver operating characteristic curve were 0.625, 0.673, and 0.703 (P < .05), respectively. VTN levels in sera may be used as a potential marker of PCa for the diagnosis and assessment of disease progression and metastasis. The combined detection of VTN and PSA in sera can be clinically applied in PCa diagnosis. .

ANALYSIS OF TMEFF2 ALLOGRAFTS AND TRANSGENIC MOUSE MODELS REVEALS ROLES IN PROSTATE REGENERATION AND CANCER

PubMed Central

Corbin, JM.; Overcash, RF.; Wren, JD.; Coburn, A.; Tipton, GJ.; Ezzell, JA.; McNaughton, KK.; Fung, KM; Kosanke, SD.; Ruiz-Echevarria, MJ

2015-01-01

BACKGROUND Previous results from our lab indicate a tumor suppressor role for the transmembrane protein with epidermal growth factor and two follistatin motifs 2 (TMEFF2) in prostate cancer (PCa). Here, we further characterize this role and uncover new functions for TMEFF2 in cancer and adult prostate regeneration. METHODS The role of TMEFF2 was examined in PCa cells using Matrigel™ cultures and allograft models of PCa cells. In addition, we developed a transgenic mouse model that expresses TMEFF2 from a prostate specific promoter. Anatomical, histological and metabolic characterizations of the transgenic mouse prostate were conducted. The effect of TMEFF2 in prostate regeneration was studied by analyzing branching morphogenesis in the TMEFF2-expressing mouse lobes and alterations in branching morphogenesis were correlated with the metabolomic profiles of the mouse lobes. The role of TMEFF2 in prostate tumorigenesis in whole animals was investigated by crossing the TMEFF2 transgenic mice with the TRAMP mouse model of PCa and analyzing the histopathological changes in the progeny. RESULTS Ectopic expression of TMEFF2 impairs growth of PCa cells in Matrigel or allograft models. Surprisingly, while TMEFF2 expression in the TRAMP mouse did not have a significant effect on the glandular prostate epithelial lesions, the double TRAMP/TMEFF2 transgenic mice displayed an increased incidence of neuroendocrine type tumors. In addition, TMEFF2 promoted increased branching specifically in the dorsal lobe of the prostate suggesting a potential role in developmental processes. These results correlated with data indicating an alteration in the metabolic profile of the dorsal lobe of the transgenic TMEFF2 mice. CONCLUSIONS Collectively, our results confirm the tumor suppressor role of TMEFF2 and suggest that ectopic expression of TMEFF2 in mouse prostate leads to additional lobe-specific effects in prostate regeneration and tumorigenesis. This points to a complex and multifunctional role for TMEFF2 during PCa progression. PMID:26417683

Analysis of TMEFF2 allografts and transgenic mouse models reveals roles in prostate regeneration and cancer.

PubMed

Corbin, Joshua M; Overcash, Ryan F; Wren, Jonathan D; Coburn, Anita; Tipton, Greg J; Ezzell, Jennifer A; McNaughton, Kirk K; Fung, Kar-Ming; Kosanke, Stanley D; Ruiz-Echevarria, Maria J

2016-01-01

Previous results from our lab indicate a tumor suppressor role for the transmembrane protein with epidermal growth factor and two follistatin motifs 2 (TMEFF2) in prostate cancer (PCa). Here, we further characterize this role and uncover new functions for TMEFF2 in cancer and adult prostate regeneration. The role of TMEFF2 was examined in PCa cells using Matrigel(TM) cultures and allograft models of PCa cells. In addition, we developed a transgenic mouse model that expresses TMEFF2 from a prostate specific promoter. Anatomical, histological, and metabolic characterizations of the transgenic mouse prostate were conducted. The effect of TMEFF2 in prostate regeneration was studied by analyzing branching morphogenesis in the TMEFF2-expressing mouse lobes and alterations in branching morphogenesis were correlated with the metabolomic profiles of the mouse lobes. The role of TMEFF2 in prostate tumorigenesis in whole animals was investigated by crossing the TMEFF2 transgenic mice with the TRAMP mouse model of PCa and analyzing the histopathological changes in the progeny. Ectopic expression of TMEFF2 impairs growth of PCa cells in Matrigel or allograft models. Surprisingly, while TMEFF2 expression in the TRAMP mouse did not have a significant effect on the glandular prostate epithelial lesions, the double TRAMP/TMEFF2 transgenic mice displayed an increased incidence of neuroendocrine type tumors. In addition, TMEFF2 promoted increased branching specifically in the dorsal lobe of the prostate suggesting a potential role in developmental processes. These results correlated with data indicating an alteration in the metabolic profile of the dorsal lobe of the transgenic TMEFF2 mice. Collectively, our results confirm the tumor suppressor role of TMEFF2 and suggest that ectopic expression of TMEFF2 in mouse prostate leads to additional lobe-specific effects in prostate regeneration and tumorigenesis. This points to a complex and multifunctional role for TMEFF2 during PCa progression. © 2015 Wiley Periodicals, Inc.

Changes in surface area of the Böön Tsagaan and Orog lakes (Mongolia, Valley of the Lakes, 1974-2013) compared to climate and permafrost changes

NASA Astrophysics Data System (ADS)

Szumińska, Danuta

2016-07-01

The main aim of the study is the analysis of changes in surface area of lake Böön Tsagaan (45°35‧N, 99°8‧E) and lake Orog (45°3‧N, 100°44‧E) taking place in the last 40 years in the context of climate conditions and permafrost degradation. The lakes, located in Central Mongolia, at the borderline of permafrost range are fed predominantly by river waters and groundwater from the surrounding mountain areas, characterized by continuous and discontinuous permafrost occurrence - mostly the Khangai. The analysis of the Böön Tsagaan and Orog lake surface area in 1974-2013 was conducted based on satellite images, whereas climate conditions were analysed using the NOAA climate data and CRU dataset. Principal Component Analysis (PCA) was used to study the relationship patterns between the climatic factors and changes in the surface area of the lakes. A tendency for a decrease in surface area, intermittent with short episodes of resupply, was observed in both studied lakes. Climate changes recorded in the analysed period had both direct and indirect impacts on water supply to lakes. Taking into account the results of PCA analysis, the most significant factors include: fluctuation of annual precipitation, increase in air temperature and thickness of snow cover. The extended duration of snow cover in the last decades of the 20th century may constitute a key factor in relation to permafrost degradation.

Usage of K-cluster and factor analysis for grouping and evaluation the quality of olive oil in accordance with physico-chemical parameters

NASA Astrophysics Data System (ADS)

Milev, M.; Nikolova, Kr.; Ivanova, Ir.; Dobreva, M.

2015-11-01

25 olive oils were studied- different in origin and ways of extraction, in accordance with 17 physico-chemical parameters as follows: color parameters - a and b, light, fluorescence peaks, pigments - chlorophyll and β-carotene, fatty-acid content. The goals of the current study were: Conducting correlation analysis to find the inner relation between the studied indices; By applying factor analysis with the help of the method of Principal Components (PCA), to reduce the great number of variables into a few factors, which are of main importance for distinguishing the different types of olive oil;Using K-means cluster to compare and group the tested types olive oils based on their similarity. The inner relation between the studied indices was found by applying correlation analysis. A factor analysis using PCA was applied on the basis of the found correlation matrix. Thus the number of the studied indices was reduced to 4 factors, which explained 79.3% from the entire variation. The first one unified the color parameters, β-carotene and the related with oxidative products fluorescence peak - about 520 nm. The second one was determined mainly by the chlorophyll content and related to it fluorescence peak - about 670 nm. The third and the fourth factors were determined by the fatty-acid content of the samples. The third one unified the fatty-acids, which give us the opportunity to distinguish olive oil from the other plant oils - oleic, linoleic and stearin acids. The fourth factor included fatty-acids with relatively much lower content in the studied samples. It is enquired the number of clusters to be determined preliminary in order to apply the K-Cluster analysis. The variant K = 3 was worked out because the types of the olive oil were three. The first cluster unified all salad and pomace olive oils, the second unified the samples of extra virgin oilstaken as controls from producers, which were bought from the trade network. The third cluster unified samples from pomace and extra virgin oils, which distinguish one from another in accordance with their parameters from the natural olive oils, because of presence of plant oils impurities.

A new Integrated Negative Symptom structure of the Positive and Negative Syndrome Scale (PANSS) in schizophrenia using item response analysis.

PubMed

Khan, Anzalee; Lindenmayer, Jean-Pierre; Opler, Mark; Yavorsky, Christian; Rothman, Brian; Lucic, Luka

2013-10-01

Debate persists with regard to how best to categorize the syndromal dimension of negative symptoms in schizophrenia. The aim was to first review published Principle Components Analysis (PCA) of the PANSS, and extract items most frequently included in the negative domain, and secondly, to examine the quality of items using Item Response Theory (IRT) to select items that best represent a measurable dimension (or dimensions) of negative symptoms. First, 22 factor analyses and PCA met were included. Second, using a large dataset (n=7187) of participants in clinical trials with chronic schizophrenia, we extracted items loading on one or more PCA. Third, items not loading with a value of ≥ 0.5, or loading on more than one component with values of ≥ 0.5 were discarded. Fourth, resulting items were included in a non-parametric IRT and retained based on Option Characteristic Curves (OCCs) and Item Characteristic Curves (ICCs). 15 items loaded on a negative domain in at least one study, with Emotional Withdrawal loading on all studies. Non-parametric IRT retained nine items as an Integrated Negative Factor: Emotional Withdrawal, Blunted Affect, Passive/Apathetic Social Withdrawal, Poor Rapport, Lack of Spontaneity/Conversation Flow, Active Social Avoidance, Disturbance of Volition, Stereotyped Thinking and Difficulty in Abstract Thinking. This is the first study to use a psychometric IRT process to arrive at a set of negative symptom items. Future steps will include further examination of these nine items in terms of their stability, sensitivity to change, and correlations with functional and cognitive outcomes. © 2013 Elsevier B.V. All rights reserved.

Modelling the habitat suitability of cetaceans: Example of the sperm whale in the northwestern Mediterranean Sea

NASA Astrophysics Data System (ADS)

Praca, Emilie; Gannier, Alexandre; Das, Krishna; Laran, Sophie

2009-04-01

Cetaceans are mobile and spend long periods underwater. Because of this, modelling their habitat could be subject to a serious problem of false absence. Furthermore, extensive surveys at sea are time and money consuming, and presence-absence data are difficult to apply. This study compares the ability of two presence-absence and two presence-only habitat modelling methods and uses the example of the sperm whale ( Physeter macrocephalus) in the northwestern Mediterranean Sea. The data consist of summer visual and acoustical detections of sperm whales, compiled between 1998 and 2005. Habitat maps were computed using topographical and hydrological eco-geographical variables. Four methods were compared: principal component analysis (PCA), ecological niche factor analysis (ENFA), generalized linear model (GLM) and multivariate adaptive regression splines (MARS). The evaluation of the models was achieved by calculating the receiver operating characteristic (ROC) of the models and their respective area under the curve (AUC). Presence-absence methods (GLM, AUC=0.70, and MARS, AUC=0.79) presented better AUC than presence-only methods (PCA, AUC=0.58, and ENFA, AUC=0.66), but this difference was not statistically significant, except between the MARS and the PCA models. The four models showed an influence of both topographical and hydrological factors, but the resulting habitat suitability maps differed. The core habitat on the continental slope was well highlighted by the four models, while GLM and MARS maps also showed a suitable habitat in the offshore waters. Presence-absence methods are therefore recommended for modelling the habitat suitability of cetaceans, as they seem more accurate to highlight complex habitat. However, the use of presence-only techniques, in particular ENFA, could be very useful for a first model of the habitat range or when important surveys at sea are not possible.

Prediction of the wash-off of traffic related semi- and non-volatile organic compounds from urban roads under climate change influenced rainfall characteristics.

PubMed

Mahbub, Parvez; Goonetilleke, Ashantha; Ayoko, Godwin A

2012-04-30

Traffic generated semi- and non-volatile organic compounds (SVOCs and NVOCs) pose a serious threat to human and ecosystem health when washed off into receiving water bodies by stormwater. Climate change influenced rainfall characteristics makes the estimation of these pollutants in stormwater quite complex. The research study discussed in the paper developed a prediction framework for such pollutants under the dynamic influence of climate change on rainfall characteristics. It was established through principal component analysis (PCA) that the intensity and durations of low to moderate rain events induced by climate change mainly affect the wash-off of SVOCs and NVOCs from urban roads. The study outcomes were able to overcome the limitations of stringent laboratory preparation of calibration matrices by extracting uncorrelated underlying factors in the data matrices through systematic application of PCA and factor analysis (FA). Based on the initial findings from PCA and FA, the framework incorporated orthogonal rotatable central composite experimental design to set up calibration matrices and partial least square regression to identify significant variables in predicting the target SVOCs and NVOCs in four particulate fractions ranging from >300 to 1 μm and one dissolved fraction of <1 μm. For the particulate fractions in >300-1 μm range, similar distributions of predicted and observed concentrations of the target compounds from minimum to 75th percentile were achieved. The inter-event coefficient of variations for particulate fractions of >300-1 μm was 5-25%. The limited solubility of the target compounds in stormwater restricted the predictive capacity of the proposed method for the dissolved fraction of <1 μm. Copyright © 2012 Elsevier B.V. All rights reserved.

Quantitative descriptive analysis and principal component analysis for sensory characterization of Indian milk product cham-cham.

PubMed

Puri, Ritika; Khamrui, Kaushik; Khetra, Yogesh; Malhotra, Ravinder; Devraja, H C

2016-02-01

Promising development and expansion in the market of cham-cham, a traditional Indian dairy product is expected in the coming future with the organized production of this milk product by some large dairies. The objective of this study was to document the extent of variation in sensory properties of market samples of cham-cham collected from four different locations known for their excellence in cham-cham production and to find out the attributes that govern much of variation in sensory scores of this product using quantitative descriptive analysis (QDA) and principal component analysis (PCA). QDA revealed significant (p < 0.05) difference in sensory attributes of cham-cham among the market samples. PCA identified four significant principal components that accounted for 72.4 % of the variation in the sensory data. Factor scores of each of the four principal components which primarily correspond to sweetness/shape/dryness of interior, surface appearance/surface dryness, rancid and firmness attributes specify the location of each market sample along each of the axes in 3-D graphs. These findings demonstrate the utility of quantitative descriptive analysis for identifying and measuring attributes of cham-cham that contribute most to its sensory acceptability.

MAOA-a novel decision maker of apoptosis and autophagy in hormone refractory neuroendocrine prostate cancer cells

PubMed Central

Lin, Yi-Cheng; Chang, Yi-Ting; Campbell, Mel; Lin, Tzu-Ping; Pan, Chin-Chen; Lee, Hsin-Chen; Shih, Jean C.; Chang, Pei-Ching

2017-01-01

Autophagy and apoptosis are two well-controlled mechanisms regulating cell fate. An understanding of decision-making between these two pathways is in its infancy. Monoamine oxidase A (MAOA) is a mitochondrial enzyme that is well-known in psychiatric research. Emerging reports showed that overexpression MAOA is associated with prostate cancer (PCa). Here, we show that MAOA is involved in mediating neuroendocrine differentiation of PCa cells, a feature associated with hormone-refractory PCa (HRPC), a lethal type of disease. Following recent reports showing that NED of PCa requires down-regulation of repressor element-1 silencing transcription factor (REST) and activation of autophagy; we observe that MAOA is a novel direct target gene of REST. Reactive oxygen species (ROS) produced by overexpressed MAOA plays an essential role in inhibiting apoptosis and activating autophagy in NED PCa cells. MAOA inhibitors significantly reduced NED and autophagy activation of PCa cells. Our results here show MAOA as a new decision-maker for activating autophagy and MAOA inhibitors may be useful as a potential therapy for neuroendocrine tumors. PMID:28402333

MAOA-a novel decision maker of apoptosis and autophagy in hormone refractory neuroendocrine prostate cancer cells.

PubMed

Lin, Yi-Cheng; Chang, Yi-Ting; Campbell, Mel; Lin, Tzu-Ping; Pan, Chin-Chen; Lee, Hsin-Chen; Shih, Jean C; Chang, Pei-Ching

2017-04-12

Autophagy and apoptosis are two well-controlled mechanisms regulating cell fate. An understanding of decision-making between these two pathways is in its infancy. Monoamine oxidase A (MAOA) is a mitochondrial enzyme that is well-known in psychiatric research. Emerging reports showed that overexpression MAOA is associated with prostate cancer (PCa). Here, we show that MAOA is involved in mediating neuroendocrine differentiation of PCa cells, a feature associated with hormone-refractory PCa (HRPC), a lethal type of disease. Following recent reports showing that NED of PCa requires down-regulation of repressor element-1 silencing transcription factor (REST) and activation of autophagy; we observe that MAOA is a novel direct target gene of REST. Reactive oxygen species (ROS) produced by overexpressed MAOA plays an essential role in inhibiting apoptosis and activating autophagy in NED PCa cells. MAOA inhibitors significantly reduced NED and autophagy activation of PCa cells. Our results here show MAOA as a new decision-maker for activating autophagy and MAOA inhibitors may be useful as a potential therapy for neuroendocrine tumors.

The phytochemical 3,3'-diindolylmethane decreases expression of AR-controlled DNA damage repair genes through repressive chromatin modifications and is associated with DNA damage in prostate cancer cells.

PubMed

Palomera-Sanchez, Zoraya; Watson, Gregory W; Wong, Carmen P; Beaver, Laura M; Williams, David E; Dashwood, Roderick H; Ho, Emily

2017-09-01

Androgen receptor (AR) is a transcription factor involved in normal prostate physiology and prostate cancer (PCa) development. 3,3'-Diindolylmethane (DIM) is a promising phytochemical agent against PCa that affects AR activity and epigenetic regulators in PCa cells. However, whether DIM suppresses PCa via epigenetic regulation of AR target genes is unknown. We assessed epigenetic regulation of AR target genes in LNCaP PCa cells and showed that DIM treatment led to epigenetic suppression of AR target genes involved in DNA repair (PARP1, MRE11, DNA-PK). Decreased expression of these genes was accompanied by an increase in repressive chromatin marks, loss of AR occupancy and EZH2 recruitment to their regulatory regions. Decreased DNA repair gene expression was associated with an increase in DNA damage (γH2Ax) and up-regulation of genomic repeat elements LINE1 and α-satellite. Our results suggest that DIM suppresses AR-dependent gene transcription through epigenetic modulation, leading to DNA damage and genome instability in PCa cells. Published by Elsevier Inc.

Comparison of water extraction methods in Tibet based on GF-1 data

NASA Astrophysics Data System (ADS)

Jia, Lingjun; Shang, Kun; Liu, Jing; Sun, Zhongqing

2018-03-01

In this study, we compared four different water extraction methods with GF-1 data according to different water types in Tibet, including Support Vector Machine (SVM), Principal Component Analysis (PCA), Decision Tree Classifier based on False Normalized Difference Water Index (FNDWI-DTC), and PCA-SVM. The results show that all of the four methods can extract large area water body, but only SVM and PCA-SVM can obtain satisfying extraction results for small size water body. The methods were evaluated by both overall accuracy (OAA) and Kappa coefficient (KC). The OAA of PCA-SVM, SVM, FNDWI-DTC, PCA are 96.68%, 94.23%, 93.99%, 93.01%, and the KCs are 0.9308, 0.8995, 0.8962, 0.8842, respectively, in consistent with visual inspection. In summary, SVM is better for narrow rivers extraction and PCA-SVM is suitable for water extraction of various types. As for dark blue lakes, the methods using PCA can extract more quickly and accurately.

Principal components derived from CSF inflammatory profiles predict outcome in survivors after severe traumatic brain injury.

PubMed

Kumar, Raj G; Rubin, Jonathan E; Berger, Rachel P; Kochanek, Patrick M; Wagner, Amy K

2016-03-01

Studies have characterized absolute levels of multiple inflammatory markers as significant risk factors for poor outcomes after traumatic brain injury (TBI). However, inflammatory marker concentrations are highly inter-related, and production of one may result in the production or regulation of another. Therefore, a more comprehensive characterization of the inflammatory response post-TBI should consider relative levels of markers in the inflammatory pathway. We used principal component analysis (PCA) as a dimension-reduction technique to characterize the sets of markers that contribute independently to variability in cerebrospinal (CSF) inflammatory profiles after TBI. Using PCA results, we defined groups (or clusters) of individuals (n=111) with similar patterns of acute CSF inflammation that were then evaluated in the context of outcome and other relevant CSF and serum biomarkers collected days 0-3 and 4-5 post-injury. We identified four significant principal components (PC1-PC4) for CSF inflammation from days 0-3, and PC1 accounted for the greatest (31%) percentage of variance. PC1 was characterized by relatively higher CSF sICAM-1, sFAS, IL-10, IL-6, sVCAM-1, IL-5, and IL-8 levels. Cluster analysis then defined two distinct clusters, such that individuals in cluster 1 had highly positive PC1 scores and relatively higher levels of CSF cortisol, progesterone, estradiol, testosterone, brain derived neurotrophic factor (BDNF), and S100b; this group also had higher serum cortisol and lower serum BDNF. Multinomial logistic regression analyses showed that individuals in cluster 1 had a 10.9 times increased likelihood of GOS scores of 2/3 vs. 4/5 at 6 months compared to cluster 2, after controlling for covariates. Cluster group did not discriminate between mortality compared to GOS scores of 4/5 after controlling for age and other covariates. Cluster groupings also did not discriminate mortality or 12 month outcomes in multivariate models. PCA and cluster analysis establish that a subset of CSF inflammatory markers measured in days 0-3 post-TBI may distinguish individuals with poor 6-month outcome, and future studies should prospectively validate these findings. PCA of inflammatory mediators after TBI could aid in prognostication and in identifying patient subgroups for therapeutic interventions. Copyright © 2015 Elsevier Inc. All rights reserved.

SU-F-J-138: An Extension of PCA-Based Respiratory Deformation Modeling Via Multi-Linear Decomposition

DOE Office of Scientific and Technical Information (OSTI.GOV)

Iliopoulos, AS; Sun, X; Pitsianis, N

Purpose: To address and lift the limited degree of freedom (DoF) of globally bilinear motion components such as those based on principal components analysis (PCA), for encoding and modeling volumetric deformation motion. Methods: We provide a systematic approach to obtaining a multi-linear decomposition (MLD) and associated motion model from deformation vector field (DVF) data. We had previously introduced MLD for capturing multi-way relationships between DVF variables, without being restricted by the bilinear component format of PCA-based models. PCA-based modeling is commonly used for encoding patient-specific deformation as per planning 4D-CT images, and aiding on-board motion estimation during radiotherapy. However, themore » bilinear space-time decomposition inherently limits the DoF of such models by the small number of respiratory phases. While this limit is not reached in model studies using analytical or digital phantoms with low-rank motion, it compromises modeling power in the presence of relative motion, asymmetries and hysteresis, etc, which are often observed in patient data. Specifically, a low-DoF model will spuriously couple incoherent motion components, compromising its adaptability to on-board deformation changes. By the multi-linear format of extracted motion components, MLD-based models can encode higher-DoF deformation structure. Results: We conduct mathematical and experimental comparisons between PCA- and MLD-based models. A set of temporally-sampled analytical trajectories provides a synthetic, high-rank DVF; trajectories correspond to respiratory and cardiac motion factors, including different relative frequencies and spatial variations. Additionally, a digital XCAT phantom is used to simulate a lung lesion deforming incoherently with respect to the body, which adheres to a simple respiratory trend. In both cases, coupling of incoherent motion components due to a low model DoF is clearly demonstrated. Conclusion: Multi-linear decomposition can enable decoupling of distinct motion factors in high-rank DVF measurements. This may improve motion model expressiveness and adaptability to on-board deformation, aiding model-based image reconstruction for target verification. NIH Grant No. R01-184173.« less

Relevance of Occlusion Test in Endovascular Coiling of Posterior Cerebral Artery (P2 Segment) Aneurysms

PubMed Central

Jayakumar, P. N.; Desai, S.; Srikanth, S. G.; Ravishankar, S.; Kovoor, J. M. E.

2004-01-01

Summary P2 segment aneurysms are located on the posterior cerebral artery (PCA) between the junction of the posterior communicating artery with the PCA and the quadrigeminal cisternal part of the PCA. We reviewed our experience with endovascular coiling in such aneurysms. Clinical and pre-procedural data from four patients, referred for endovascular treatment of P2 segment aneurysms, were retrospectively studied for factors influencing post-interventional neurological deficits caused by ischemia of the PCA distal territory. Balloon occlusion was done in three patients and patient tolerance was assessed using clinical and anatomic criteria. Embryologic and anatomic features of the PCA were reviewed. Balloon occlusion test and endovascular coiling of aneurysms was possible in three patients. Control angiogram after embolization showed elimination of aneurysms from the circulation and the distal PCA filled through leptomeningeal anastomoses. One patient deteriorated due to aneurysmal rupture soon after the balloon occlusion test and coiling could not be done. In the other three patients post-intervention CT and MRI images showed PCA territory infarcts in spite of demonstration of good collateral circulation distal to the occluded PCA. In conclusion, P2 aneurysms can be effectively treated by endovascular coiling without a balloon occlusion test. While the balloon occlusion test does not contribute to clinical decision-making it may be associated with potential morbidity and mortality. PMID:20587236

Waist-hip Ratio (WHR), a Better Predictor for Prostate Cancer than Body Mass Index (BMI): Results from a Chinese Hospital-based Biopsy Cohort.

PubMed

Tang, Bo; Han, Cheng-Tao; Zhang, Gui-Ming; Zhang, Cui-Zhu; Yang, Wei-Yi; Shen, Ying; Vidal, Adriana C; Freedland, Stephen J; Zhu, Yao; Ye, Ding-Wei

2017-03-08

To investigate whether waist-hip ratio (WHR) is a better predictor of prostate cancer (PCa) incidence than body mass index (BMI) in Chinese men. Of consecutive patients who underwent prostate biopsies in one tertiary center between 2013 and 2015, we examined data on 1018 with PSA ≤20 ng/ml. Clinical data and biopsy outcomes were collected. Logistic regression was used to evaluate the associations between BMI, WHR and PCa incidence. Area under the ROC (AUC) was used to evaluate the accuracy of different prognostic models. A total of 255 men and 103 men were diagnosed with PCa and high grade PCa (HGPCa, Gleason score ≥8). WHR was an independent risk factor for both PCa (OR = 1.07 95%Cl 1.03-1.11) and HGPCa (OR = 1.14 95%Cl 1.09-1.19) detection, while BMI had no relationship with either PCa or HGPCa detection. Adding WHR to a multivariable model increased the AUC for detecting HGPCa from 0.66 (95%Cl 0.60-0.72) to 0.71 (95%Cl 0.65-0.76). In this Chinese cohort, WHR was significantly predictive of PCa and HGPCa. Adding WHR to a multivariable model increased the diagnostic accuracy for detecting HGPCa. If confirmed, including WHR measurement may improve PCa and HGPCa detection.

Waist-hip Ratio (WHR), a Better Predictor for Prostate Cancer than Body Mass Index (BMI): Results from a Chinese Hospital-based Biopsy Cohort

PubMed Central

Tang, Bo; Han, Cheng-Tao; Zhang, Gui-Ming; Zhang, Cui-Zhu; Yang, Wei-Yi; Shen, Ying; Vidal, Adriana C.; Freedland, Stephen J.; Zhu, Yao; Ye, Ding-Wei

2017-01-01

To investigate whether waist-hip ratio (WHR) is a better predictor of prostate cancer (PCa) incidence than body mass index (BMI) in Chinese men. Of consecutive patients who underwent prostate biopsies in one tertiary center between 2013 and 2015, we examined data on 1018 with PSA ≤20 ng/ml. Clinical data and biopsy outcomes were collected. Logistic regression was used to evaluate the associations between BMI, WHR and PCa incidence. Area under the ROC (AUC) was used to evaluate the accuracy of different prognostic models. A total of 255 men and 103 men were diagnosed with PCa and high grade PCa (HGPCa, Gleason score ≥8). WHR was an independent risk factor for both PCa (OR = 1.07 95%Cl 1.03–1.11) and HGPCa (OR = 1.14 95%Cl 1.09–1.19) detection, while BMI had no relationship with either PCa or HGPCa detection. Adding WHR to a multivariable model increased the AUC for detecting HGPCa from 0.66 (95%Cl 0.60–0.72) to 0.71 (95%Cl 0.65–0.76). In this Chinese cohort, WHR was significantly predictive of PCa and HGPCa. Adding WHR to a multivariable model increased the diagnostic accuracy for detecting HGPCa. If confirmed, including WHR measurement may improve PCa and HGPCa detection. PMID:28272469

Fast and Accurate Radiative Transfer Calculations Using Principal Component Analysis for (Exo-)Planetary Retrieval Models

NASA Astrophysics Data System (ADS)

Kopparla, P.; Natraj, V.; Shia, R. L.; Spurr, R. J. D.; Crisp, D.; Yung, Y. L.

2015-12-01

Radiative transfer (RT) computations form the engine of atmospheric retrieval codes. However, full treatment of RT processes is computationally expensive, prompting usage of two-stream approximations in current exoplanetary atmospheric retrieval codes [Line et al., 2013]. Natraj et al. [2005, 2010] and Spurr and Natraj [2013] demonstrated the ability of a technique using principal component analysis (PCA) to speed up RT computations. In the PCA method for RT performance enhancement, empirical orthogonal functions are developed for binned sets of inherent optical properties that possess some redundancy; costly multiple-scattering RT calculations are only done for those few optical states corresponding to the most important principal components, and correction factors are applied to approximate radiation fields. Kopparla et al. [2015, in preparation] extended the PCA method to a broadband spectral region from the ultraviolet to the shortwave infrared (0.3-3 micron), accounting for major gas absorptions in this region. Here, we apply the PCA method to a some typical (exo-)planetary retrieval problems. Comparisons between the new model, called Universal Principal Component Analysis Radiative Transfer (UPCART) model, two-stream models and line-by-line RT models are performed, for spectral radiances, spectral fluxes and broadband fluxes. Each of these are calculated at the top of the atmosphere for several scenarios with varying aerosol types, extinction and scattering optical depth profiles, and stellar and viewing geometries. We demonstrate that very accurate radiance and flux estimates can be obtained, with better than 1% accuracy in all spectral regions and better than 0.1% in most cases, as compared to a numerically exact line-by-line RT model. The accuracy is enhanced when the results are convolved to typical instrument resolutions. The operational speed and accuracy of UPCART can be further improved by optimizing binning schemes and parallelizing the codes, work on which is under way.

Proteomics analysis of malignant and benign prostate tissue by 2D DIGE/MS reveals new insights into proteins involved in prostate cancer.

PubMed

Davalieva, Katarina; Kostovska, Ivana Maleva; Kiprijanovska, Sanja; Markoska, Katerina; Kubelka-Sabit, Katerina; Filipovski, Vanja; Stavridis, Sotir; Stankov, Oliver; Komina, Selim; Petrusevska, Gordana; Polenakovic, Momir

2015-10-01

The key to a more effective diagnosis, prognosis, and therapeutic management of prostate cancer (PCa) could lie in the direct analysis of cancer tissue. In this study, by comparative proteomics analysis of PCa and benign prostate hyperplasia (BPH) tissues we attempted to elucidate the proteins and regulatory pathways involved in this disease. The samples used in this study were fresh surgical tissues with clinically and histologically confirmed PCa (n = 19) and BPH (n = 33). We used two dimensional difference in gel electrophoresis (2D DIGE) coupled with mass spectrometry (MS) and bioinformatics analysis. Thirty-nine spots with statistically significant 1.8-fold variation or more in abundance, corresponding to 28 proteins were identified. The IPA analysis pointed out to 3 possible networks regulated within MAPK, ERK, TGFB1, and ubiquitin pathways. Thirteen of the identified proteins, namely, constituents of the intermediate filaments (KRT8, KRT18, DES), potential tumor suppressors (ARHGAP1, AZGP1, GSTM2, and MFAP4), transport and membrane organization proteins (FABP5, GC, and EHD2), chaperons (FKBP4 and HSPD1) and known cancer marker (NME1) have been associated with prostate and other cancers by numerous proteomics, genomics or functional studies. We evidenced for the first time the dysregulation of 9 proteins (CSNK1A1, ARID5B, LYPLA1, PSMB6, RABEP1, TALDO1, UBE2N, PPP1CB, and SERPINB1) that may have role in PCa. The UBE2N, PSMB6, and PPP1CB, involved in cell cycle regulation and progression were evaluated by Western blot analysis which confirmed significantly higher abundances of UBE2N and PSMB6 and significantly lower abundance of PPP1CB in PCa. In addition to the identification of substantial number of proteins with known association with PCa, the proteomic approach in this study revealed proteins not previously clearly related to PCa, providing a starting point for further elucidation of their function in disease initiation and progression. © 2015 Wiley Periodicals, Inc.

TLR3 engagement induces IRF-3-dependent apoptosis in androgen-sensitive prostate cancer cells and inhibits tumour growth in vivo

PubMed Central

Gambara, Guido; Desideri, Marianna; Stoppacciaro, Antonella; Padula, Fabrizio; De Cesaris, Paola; Starace, Donatella; Tubaro, Andrea; del Bufalo, Donatella; Filippini, Antonio; Ziparo, Elio; Riccioli, Anna

2015-01-01

Toll-like receptors (TLRs) are a family of highly conserved transmembrane proteins expressed in epithelial and immune cells that recognize pathogen associated molecular patterns. Besides their role in immune response against infections, numerous studies have shown an important role of different TLRs in cancer, indicating these receptors as potential targets for cancer therapy. We previously demonstrated that the activation of TLR3 by the synthetic double-stranded RNA analogue poly I:C induces apoptosis of androgen-sensitive prostate cancer (PCa) LNCaP cells and, much less efficiently, of the more aggressive PC3 cell line. Therefore, in this study we selected LNCaP cells to investigate the mechanism of TLR3-mediated apoptosis and the in vivo efficacy of poly I:C-based therapy. We show that interferon regulatory factor-3 (IRF-3) signalling plays an essential role in TLR3-mediated apoptosis in LNCaP cells through the activation of the intrinsic and extrinsic apoptotic pathways. Interestingly, hardly any apoptosis was induced by poly I:C in normal prostate epithelial cells RWPE-1. We also demonstrate for the first time the direct anticancer effect of poly I:C as a single therapeutic agent in a well-established human androgen-sensitive PCa xenograft model, by showing that tumour growth is highly impaired in poly I:C-treated immunodeficient mice. Immunohistochemical analysis of PCa xenografts highlights the antitumour role of poly I:C in vivo both on cancer cells and, indirectly, on endothelial cells. Notably, we show the presence of TLR3 and IRF-3 in both human normal and PCa clinical samples, potentially envisaging poly I:C-based therapy for PCa. PMID:25444175

Gait dynamics to optimize fall risk assessment in geriatric patients admitted to an outpatient diagnostic clinic

PubMed Central

de Groot, Maartje H.; van Campen, Jos P.; Beijnen, Jos H.; Hortobágyi, Tibor; Vuillerme, Nicolas; Lamoth, Claudine C. J.

2017-01-01

Fall prediction in geriatric patients remains challenging because the increased fall risk involves multiple, interrelated factors caused by natural aging and/or pathology. Therefore, we used a multi-factorial statistical approach to model categories of modifiable fall risk factors among geriatric patients to identify fallers with highest sensitivity and specificity with a focus on gait performance. Patients (n = 61, age = 79; 41% fallers) underwent extensive screening in three categories: (1) patient characteristics (e.g., handgrip strength, medication use, osteoporosis-related factors) (2) cognitive function (global cognition, memory, executive function), and (3) gait performance (speed-related and dynamic outcomes assessed by tri-axial trunk accelerometry). Falls were registered prospectively (mean follow-up 8.6 months) and one year retrospectively. Principal Component Analysis (PCA) on 11 gait variables was performed to determine underlying gait properties. Three fall-classification models were then built using Partial Least Squares–Discriminant Analysis (PLS-DA), with separate and combined analyses of the fall risk factors. PCA identified ‘pace’, ‘variability’, and ‘coordination’ as key properties of gait. The best PLS-DA model produced a fall classification accuracy of AUC = 0.93. The specificity of the model using patient characteristics was 60% but reached 80% when cognitive and gait outcomes were added. The inclusion of cognition and gait dynamics in fall classification models reduced misclassification. We therefore recommend assessing geriatric patients’ fall risk using a multi-factorial approach that incorporates patient characteristics, cognition, and gait dynamics. PMID:28575126

Gait dynamics to optimize fall risk assessment in geriatric patients admitted to an outpatient diagnostic clinic.

PubMed

Kikkert, Lisette H J; de Groot, Maartje H; van Campen, Jos P; Beijnen, Jos H; Hortobágyi, Tibor; Vuillerme, Nicolas; Lamoth, Claudine C J

2017-01-01

Fall prediction in geriatric patients remains challenging because the increased fall risk involves multiple, interrelated factors caused by natural aging and/or pathology. Therefore, we used a multi-factorial statistical approach to model categories of modifiable fall risk factors among geriatric patients to identify fallers with highest sensitivity and specificity with a focus on gait performance. Patients (n = 61, age = 79; 41% fallers) underwent extensive screening in three categories: (1) patient characteristics (e.g., handgrip strength, medication use, osteoporosis-related factors) (2) cognitive function (global cognition, memory, executive function), and (3) gait performance (speed-related and dynamic outcomes assessed by tri-axial trunk accelerometry). Falls were registered prospectively (mean follow-up 8.6 months) and one year retrospectively. Principal Component Analysis (PCA) on 11 gait variables was performed to determine underlying gait properties. Three fall-classification models were then built using Partial Least Squares-Discriminant Analysis (PLS-DA), with separate and combined analyses of the fall risk factors. PCA identified 'pace', 'variability', and 'coordination' as key properties of gait. The best PLS-DA model produced a fall classification accuracy of AUC = 0.93. The specificity of the model using patient characteristics was 60% but reached 80% when cognitive and gait outcomes were added. The inclusion of cognition and gait dynamics in fall classification models reduced misclassification. We therefore recommend assessing geriatric patients' fall risk using a multi-factorial approach that incorporates patient characteristics, cognition, and gait dynamics.

Evaluation of redundancy analysis to identify signatures of local adaptation.

PubMed

Capblancq, Thibaut; Luu, Keurcien; Blum, Michael G B; Bazin, Eric

2018-05-26

Ordination is a common tool in ecology that aims at representing complex biological information in a reduced space. In landscape genetics, ordination methods such as principal component analysis (PCA) have been used to detect adaptive variation based on genomic data. Taking advantage of environmental data in addition to genotype data, redundancy analysis (RDA) is another ordination approach that is useful to detect adaptive variation. This paper aims at proposing a test statistic based on RDA to search for loci under selection. We compare redundancy analysis to pcadapt, which is a nonconstrained ordination method, and to a latent factor mixed model (LFMM), which is a univariate genotype-environment association method. Individual-based simulations identify evolutionary scenarios where RDA genome scans have a greater statistical power than genome scans based on PCA. By constraining the analysis with environmental variables, RDA performs better than PCA in identifying adaptive variation when selection gradients are weakly correlated with population structure. Additionally, we show that if RDA and LFMM have a similar power to identify genetic markers associated with environmental variables, the RDA-based procedure has the advantage to identify the main selective gradients as a combination of environmental variables. To give a concrete illustration of RDA in population genomics, we apply this method to the detection of outliers and selective gradients on an SNP data set of Populus trichocarpa (Geraldes et al., 2013). The RDA-based approach identifies the main selective gradient contrasting southern and coastal populations to northern and continental populations in the northwestern American coast. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Combined serum and EPS-urine proteomic analysis using iTRAQ technology for discovery of potential prostate cancer biomarkers.

PubMed

Zhang, Mo; Chen, Lizhu; Yuan, Zhengwei; Yang, Zeyu; Li, Yue; Shan, Liping; Yin, Bo; Fei, Xiang; Miao, Jianing; Song, Yongsheng

2016-11-01

Prostate cancer (PCa) is one of the most common malignant tumors and a major cause of cancer-related death for men worldwide. The aim of our study was to identify potential non-invasive serum and expressed prostatic secretion (EPS)-urine biomarkers for accurate diagnosis of PCa. Here, we performed a combined isobaric tags for relative and absolute quantification (iTRAQ) proteomic analysis to compare protein profiles using pooled serum and EPS-urine samples from 4 groups of patients: benign prostate hyperplasia (BPH), high grade prostatic intraepithelial neoplasia (HGPIN), localized PCa and metastatic PCa. The differentially expressed proteins were rigorously selected and further validated in a large and independent cohort using classical ELISA and Western blot assays. Finally, we established a multiplex biomarker panel consisting of 3 proteins (serum PF4V1, PSA, and urinary CRISP3) with an excellent diagnostic capacity to differentiate PCa from BPH [area under the receiver operating characteristic curve (AUC) of 0.941], which showed an evidently greater discriminatory ability than PSA alone (AUC, 0.757) (P<0.001). Importantly, even when PSA level was in the gray zone (4-10 ng/mL), a combination of PF4V1 and CRISP3 could achieve a relatively high diagnostic efficacy (AUC, 0.895). Furthermore, their combination also had the potential to distinguish PCa from HGPIN (AUC, 0.934). Our results demonstrated that the combined application of serum and EPS-urine biomarkers can improve the diagnosis of PCa and provide a new prospect for non-invasive PCa detection.

Role of Epithelial Mesenchymal Transition in Prostate Tumorigenesis

PubMed Central

Khan, Mohammad Imran; Hamid, Abid; Adhami, Vaqar Mustafa; Lall, Rahul K; Mukhtar, Hasan

2015-01-01

Globally, the cancer associated deaths are generally attributed to the spread of cancerous cells or their features to the nearby or distant secondary organs by a process known as metastasis. Among other factors, the metastatic dissemination of cancer cells is attributed to the reactivation of an evolutionary conserved developmental program known as epithelial to mesenchymal transition (EMT). During EMT, fully differentiated epithelial cells undergo a series of dramatic changes in their morphology, along with loss of cell to cell contact and matrix remodeling into less differentiated and invasive mesenchymal cells. Many studies provide evidence for the existence of EMT like states in prostate cancer (PCa) and suggest its possible involvement in PCa progression and metastasis. At the same time, the lack of conclusive evidence regarding the presence of full EMT in human PCa samples has somewhat dampened the interest in the field. However, ongoing EMT research provides new perspectives and unveils the enormous potential of this field in tailoring new therapeutic regimens for PCa management. This review summarizes the role of many transcription factors and other molecules that drive EMT during prostate tumorigenesis. PMID:25506896

The NLR-related protein NWD1 is associated with prostate cancer and modulates androgen receptor signaling.

PubMed

Correa, Ricardo G; Krajewska, Maryla; Ware, Carl F; Gerlic, Motti; Reed, John C

2014-03-30

Prostate cancer (PCa) is among the leading causes of cancer-related death in men. Androgen receptor (AR) signaling plays a seminal role in prostate development and homeostasis, and dysregulation of this pathway is intimately linked to prostate cancer pathogenesis and progression. Here, we identify the cytosolic NLR-related protein NWD1 as a novel modulator of AR signaling. We determined that expression of NWD1 becomes elevated during prostate cancer progression, based on analysis of primary tumor specimens. Experiments with cultured cells showed that NWD1 expression is up-regulated by the sex-determining region Y (SRY) family proteins. Gene silencing procedures, in conjunction with transcriptional profiling, showed that NWD1 is required for expression of PDEF (prostate-derived Ets factor), which is known to bind and co-regulate AR. Of note, NWD1 modulates AR protein levels. Depleting NWD1 in PCa cell lines reduces AR levels and suppresses activity of androgen-driven reporter genes. NWD1 knockdown potently suppressed growth of androgen-dependent LNCaP prostate cancer cells, thus showing its functional importance in an AR-dependent tumor cell model. Proteomic analysis suggested that NWD1 associates with various molecular chaperones commonly related to AR complexes. Altogether, these data suggest a role for tumor-associated over-expression of NWD1 in dysregulation of AR signaling in PCa.

Flight test of a propulsion controlled aircraft system on the NASA F-15 airplane

NASA Technical Reports Server (NTRS)

Burcham, Frank W., Jr.; Maine, Trindel A.

1995-01-01

Flight tests of the propulsion controlled aircraft (PCA) system on the NASA F-15 airplane evolved as a result of a long series of simulation and flight tests. Initially, the simulation results were very optimistic. Early flight tests showed that manual throttles-only control was much more difficult than the simulation, and a flight investigation was flown to acquire data to resolve this discrepancy. The PCA system designed and developed by MDA evolved as these discrepancies were found and resolved, requiring redesign of the PCA software and modification of the flight test plan. Small throttle step inputs were flown to provide data for analysis, simulation update, and control logic modification. The PCA flight tests quickly revealed less than desired performance, but the extensive flexibility built into the flight PCA software allowed rapid evaluation of alternate gains, filters, and control logic, and within 2 weeks, the PCA system was functioning well. The initial objective of achieving adequate control for up-and-away flying and approaches was satisfied, and the option to continue to actual landings was achieved. After the PCA landings were accomplished, other PCA features were added, and additional maneuvers beyond those originally planned were flown. The PCA system was used to recover from extreme upset conditions, descend, and make approaches to landing. A heading mode was added, and a single engine plus rudder PCA mode was also added and flown. The PCA flight envelope was expanded far beyond that originally designed for. Guest pilots from the USAF, USN, NASA, and the contractor also flew the PCA system and were favorably impressed.

An In Vitro Spectroscopic Analysis to Determine Whether para-Chloroaniline is Produced from Mixing Sodium Hypochlorite and Chlorhexidine

PubMed Central

Thomas, John E.; Sem, Daniel S.

2009-01-01

Introduction The purpose of this in vitro study was to determine whether para-chloroaniline (PCA) is formed through the reaction of mixing sodium hypochlorite (NaOCl) and chlorhexidine (CHX). Methods Initially commercially available samples of chlorhexidine acetate (CHXa) and PCA were analyzed with 1H NMR spectroscopy. Two solutions, NaOCl and CHXa, were warmed to 37°C and when mixed they produced a brown precipitate. This precipitate was separated in half and pure PCA was added to one of the samples for comparison before they were each analyzed with 1H NMR spectroscopy. Results The peaks in the 1H NMR spectra of CHXa and PCA were assigned to specific protons of the molecules, and the location of the aromatic peaks in the PCA spectrum defined the PCA doublet region. While the spectrum of the precipitate alone resulted in a complex combination of peaks, upon magnification there were no peaks in the PCA doublet region which were intense enough to be quantified. In the spectrum of the precipitate, to which PCA was added, two peaks do appear in the PCA doublet region. Comparing this spectrum to that of precipitate alone, the peaks in the PCA doublet region are not visible prior to the addition of PCA. Conclusions Based on this in vitro study, the reaction mixture of NaOCl and CHXa does not produce PCA at any measurable quantity and further investigation is needed to determine the chemical composition of the brown precipitate. PMID:20113799

Direct analysis in real time mass spectrometry and multivariate data analysis: a novel approach to rapid identification of analytical markers for quality control of traditional Chinese medicine preparation.

PubMed

Zeng, Shanshan; Wang, Lu; Chen, Teng; Wang, Yuefei; Mo, Huanbiao; Qu, Haibin

2012-07-06

The paper presents a novel strategy to identify analytical markers of traditional Chinese medicine preparation (TCMP) rapidly via direct analysis in real time mass spectrometry (DART-MS). A commonly used TCMP, Danshen injection, was employed as a model. The optimal analysis conditions were achieved by measuring the contribution of various experimental parameters to the mass spectra. Salvianolic acids and saccharides were simultaneously determined within a single 1-min DART-MS run. Furthermore, spectra of Danshen injections supplied by five manufacturers were processed with principal component analysis (PCA). Obvious clustering was observed in the PCA score plot, and candidate markers were recognized from the contribution plots of PCA. The suitability of potential markers was then confirmed by contrasting with the results of traditional analysis methods. Using this strategy, fructose, glucose, sucrose, protocatechuic aldehyde and salvianolic acid A were rapidly identified as the markers of Danshen injections. The combination of DART-MS with PCA provides a reliable approach to the identification of analytical markers for quality control of TCMP. Copyright © 2012 Elsevier B.V. All rights reserved.

PCA based clustering for brain tumor segmentation of T1w MRI images.

PubMed

Kaya, Irem Ersöz; Pehlivanlı, Ayça Çakmak; Sekizkardeş, Emine Gezmez; Ibrikci, Turgay

2017-03-01

Medical images are huge collections of information that are difficult to store and process consuming extensive computing time. Therefore, the reduction techniques are commonly used as a data pre-processing step to make the image data less complex so that a high-dimensional data can be identified by an appropriate low-dimensional representation. PCA is one of the most popular multivariate methods for data reduction. This paper is focused on T1-weighted MRI images clustering for brain tumor segmentation with dimension reduction by different common Principle Component Analysis (PCA) algorithms. Our primary aim is to present a comparison between different variations of PCA algorithms on MRIs for two cluster methods. Five most common PCA algorithms; namely the conventional PCA, Probabilistic Principal Component Analysis (PPCA), Expectation Maximization Based Principal Component Analysis (EM-PCA), Generalize Hebbian Algorithm (GHA), and Adaptive Principal Component Extraction (APEX) were applied to reduce dimensionality in advance of two clustering algorithms, K-Means and Fuzzy C-Means. In the study, the T1-weighted MRI images of the human brain with brain tumor were used for clustering. In addition to the original size of 512 lines and 512 pixels per line, three more different sizes, 256 × 256, 128 × 128 and 64 × 64, were included in the study to examine their effect on the methods. The obtained results were compared in terms of both the reconstruction errors and the Euclidean distance errors among the clustered images containing the same number of principle components. According to the findings, the PPCA obtained the best results among all others. Furthermore, the EM-PCA and the PPCA assisted K-Means algorithm to accomplish the best clustering performance in the majority as well as achieving significant results with both clustering algorithms for all size of T1w MRI images. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

[Analyzing and modeling methods of near infrared spectroscopy for in-situ prediction of oil yield from oil shale].

PubMed

Liu, Jie; Zhang, Fu-Dong; Teng, Fei; Li, Jun; Wang, Zhi-Hong

2014-10-01

In order to in-situ detect the oil yield of oil shale, based on portable near infrared spectroscopy analytical technology, with 66 rock core samples from No. 2 well drilling of Fuyu oil shale base in Jilin, the modeling and analyzing methods for in-situ detection were researched. By the developed portable spectrometer, 3 data formats (reflectance, absorbance and K-M function) spectra were acquired. With 4 different modeling data optimization methods: principal component-mahalanobis distance (PCA-MD) for eliminating abnormal samples, uninformative variables elimination (UVE) for wavelength selection and their combina- tions: PCA-MD + UVE and UVE + PCA-MD, 2 modeling methods: partial least square (PLS) and back propagation artificial neural network (BPANN), and the same data pre-processing, the modeling and analyzing experiment were performed to determine the optimum analysis model and method. The results show that the data format, modeling data optimization method and modeling method all affect the analysis precision of model. Results show that whether or not using the optimization method, reflectance or K-M function is the proper spectrum format of the modeling database for two modeling methods. Using two different modeling methods and four different data optimization methods, the model precisions of the same modeling database are different. For PLS modeling method, the PCA-MD and UVE + PCA-MD data optimization methods can improve the modeling precision of database using K-M function spectrum data format. For BPANN modeling method, UVE, UVE + PCA-MD and PCA- MD + UVE data optimization methods can improve the modeling precision of database using any of the 3 spectrum data formats. In addition to using the reflectance spectra and PCA-MD data optimization method, modeling precision by BPANN method is better than that by PLS method. And modeling with reflectance spectra, UVE optimization method and BPANN modeling method, the model gets the highest analysis precision, its correlation coefficient (Rp) is 0.92, and its standard error of prediction (SEP) is 0.69%.

Low-Molecular-Weight Protein Tyrosine Phosphatase Predicts Prostate Cancer Outcome by Increasing the Metastatic Potential.

PubMed

Ruela-de-Sousa, Roberta R; Hoekstra, Elmer; Hoogland, A Marije; Queiroz, Karla C Souza; Peppelenbosch, Maikel P; Stubbs, Andrew P; Pelizzaro-Rocha, Karin; van Leenders, Geert J L H; Jenster, Guido; Aoyama, Hiroshi; Ferreira, Carmen V; Fuhler, Gwenny M

2016-04-01

Low-risk patients suffering from prostate cancer (PCa) are currently placed under active surveillance rather than undergoing radical prostatectomy. However, clear parameters for selecting the right patient for each strategy are not available, and new biomarkers and treatment modalities are needed. Low-molecular-weight protein tyrosine phosphatase (LMWPTP) could present such a target. To correlate expression levels of LMWPTP in primary PCa to clinical outcome, and determine the role of LMWPTP in prostate tumor cell biology. Acid phosphatase 1, soluble (ACP1) expression was analyzed on microarray data sets, which were subsequently used in Ingenuity Pathway Analysis. Immunohistochemistry was performed on a tissue microarray containing material of 481 PCa patients whose clinicopathologic data were recorded. PCa cell line models were used to investigate the role of LMWPTP in cell proliferation, migration, adhesion, and anoikis resistance. The association between LMWPTP expression and clinical and pathologic outcomes was calculated using chi-square correlations and multivariable Cox regression analysis. Functional consequences of LMWPTP overexpression or downregulation were determined using migration and adhesion assays, confocal microscopy, Western blotting, and proliferation assays. LMWPTP expression was significantly increased in human PCa and correlated with earlier recurrence of disease (hazard ratio [HR]:1.99; p<0.001) and reduced patient survival (HR: 1.53; p=0.04). Unbiased Ingenuity analysis comparing cancer and normal prostate suggests migratory propensities in PCa. Indeed, overexpression of LMWPTP increases PCa cell migration, anoikis resistance, and reduces activation of focal adhesion kinase/paxillin, corresponding to decreased adherence. Overexpression of LMWPTP in PCa confers a malignant phenotype with worse clinical outcome. Prospective follow-up should determine the clinical potential of LMWPTP overexpression. These findings implicate low-molecular-weight protein tyrosine phosphatase as a novel oncogene in prostate cancer and could offer the possibility of using this protein as biomarker or target for treatment of this disease. Copyright © 2015 European Association of Urology. Published by Elsevier B.V. All rights reserved.

Ecological correlates of the non-indigenous parasitoid assemblage associated with a Hawaiian endemic moth.

PubMed

Kaufman, Leyla V; Wright, Mark G

2011-08-01

Understanding what ecological factors might predispose indigenous habitats to invasion by invasive species is an important aspect of conservation and invasive species management, particularly when biological control is considered for suppression of the invasive species. This study seeks to identify ecological factors that might play a role in determining the structure of the parasitoid assemblage associated with caterpillars of the endemic Hawaiian moth Udea stellata (Crambidae). Parasitoids were reared from field-collected U. stellata larvae at 18 locations. Fourteen environmental variables were measured at each site. Two multivariate analyses, principal component analysis (PCA) and partial redundancy analysis (RDA), were used to analyze the parasitoid assemblage across a range of habitats varying in environmental characteristics. The PCA analysis showed that the occurrence of some species were highly correlated, and associated with less disturbed sites, whereas other species were associated with sites of medium and high levels of disturbance. The RDA analysis showed that only three of the measured environmental variables (U. stellata density, elevation, and level of habitat disturbance) significantly explained variability in the parasitoid assemblage among sites. There was greater parasitoid species richness associated with U. stellata larvae at higher elevation sites with a lower degree of habitat disturbance by exotic vegetation. The purposely introduced parasitoid species were associated with the non-target moth at sites located at higher elevations with low levels of disturbance. Multivariate analysis has the potential to provide valuable insights into the identification of important environmental factors that mediate parasitoid assemblage structure and level of parasitism on a particular target or non-target species, and therefore facilitate identification of suitable target habitats or susceptible non-target habitats.

Causes of Death in Men With Prevalent Diabetes and Newly Diagnosed High- Versus Favorable-Risk Prostate Cancer

DOE Office of Scientific and Technical Information (OSTI.GOV)

D'Amico, Anthony V., E-mail: adamico@partners.or; Braccioforte, Michelle H.; Moran, Brian J.

2010-08-01

Purpose: To determine whether prevalent diabetes mellitus (pDM) affects the presentation, extent of radiotherapy, or prostate cancer (PCa)-specific mortality (PCSM) and whether PCa aggressiveness affects the risk of non-PCSM, DM-related mortality, and all-cause mortality in men with pDM. Methods: Between October 1997 and July 2907, 5,279 men treated at the Chicago Prostate Cancer Center with radiotherapy for PCa were included in the study. Logistic and competing risk regression analyses were performed to assess whether pDM was associated with high-grade PCa, less aggressive radiotherapy, and an increased risk of PCSM. Competing risks and Cox regression analyses were performed to assess whethermore » PCa aggressiveness described by risk group in men with pDM was associated with the risk of non-PCSM, DM-related mortality, and all-cause mortality. Analyses were adjusted for predictors of high-grade PCa and factors that could affect treatment extent and mortality. Results: Men with pDM were more likely (adjusted hazard ratio [AHR], 1.9; 95% confidence interval [CI], 1.3-2.7; p = .002) to present with high-grade PCa but were not treated less aggressively (p = .33) and did not have an increased risk of PCSM (p = .58) compared to men without pDM. Among the men with pDM, high-risk PCa was associated with a greater risk of non-PCSM (AHR, 2.2; 95% CI, 1.1-4.5; p = .035), DM-related mortality (AHR, 5.2; 95% CI, 2.0-14.0; p = .001), and all-cause mortality (AHR, 2.4; 95% CI, 1.2-4.7; p = .01) compared to favorable-risk PCa. Conclusion: Aggressive management of pDM is warranted in men with high-risk PCa.« less

Risk of Localized and Advanced Prostate Cancer Among Immigrants Versus Native-Born Swedish Men: A nation-wide, population-based study

PubMed Central

Loeb, Stacy; Drevin, Linda; Robinson, David; Holmberg, Erik; Carlsson, Sigrid; Lambe, Mats; Stattin, Pär

2016-01-01

Purpose Prostate cancer (PCa) incidence and prognosis vary geographically. We examined possible differences in PCa risk by clinical risk category between native-born and immigrant populations in Sweden. Our hypothesis was that lower PSA-testing uptake among foreign-born men would result in lower rates of localized disease, and similar or higher risk of metastatic disease. Methods Using the Prostate Cancer database Sweden (PCBaSe), we identified 117,328 men with PCa diagnosed from 1991–2008, of which 8,332 were foreign-born. For each case, 5 cancer-free matched controls were randomly selected from the population register. Conditional logistic regression was used to compare low-risk, intermediate-risk, high-risk, regionally metastatic, and distant metastatic PCa based upon region of origin. Results Across all risk categories, immigrants had significantly lower PCa risk than native-born Swedish men, except North Americans and Northern Europeans. The lowest PCa risk was observed in men from the Middle East, Southern Europe and Asia. Multivariable adjustment for socioeconomic factors and comorbidities did not materially change risk estimates. Older age at immigration and more recent arrival in Sweden were associated with lower PCa risk. Non-native men were less likely to be diagnosed with PCa through PSA-testing during a health check-up. Conclusions The risk for all stages of PCa was lower among first-generation immigrants to Sweden compared to native-born men. Older age at immigration and more recent immigration were associated with particularly low risks. Patterns of PSA testing appeared to only partly explain the differences in PCa risk, since immigrant men also had a lower risk of metastatic disease. PMID:23266834

Contrast-Enhanced Ultrasound (CEUS) and Quantitative Perfusion Analysis in Patients with Suspicion for Prostate Cancer.

PubMed

Maxeiner, Andreas; Fischer, Thomas; Schwabe, Julia; Baur, Alexander Daniel Jacques; Stephan, Carsten; Peters, Robert; Slowinski, Torsten; von Laffert, Maximilian; Marticorena Garcia, Stephan Rodrigo; Hamm, Bernd; Jung, Ernst-Michael

2018-06-06

 The aim of this study was to investigate contrast-enhanced ultrasound (CEUS) parameters acquired by software during magnetic resonance imaging (MRI) US fusion-guided biopsy for prostate cancer (PCa) detection and discrimination.  From 2012 to 2015, 158 out of 165 men with suspicion for PCa and with at least 1 negative biopsy of the prostate were included and underwent a multi-parametric 3 Tesla MRI and an MRI/US fusion-guided biopsy, consecutively. CEUS was conducted during biopsy with intravenous bolus application of 2.4 mL of SonoVue ® (Bracco, Milan, Italy). In the latter CEUS clips were investigated using quantitative perfusion analysis software (VueBox, Bracco). The area of strongest enhancement within the MRI pre-located region was investigated and all available parameters from the quantification tool box were collected and analyzed for PCa and its further differentiation was based on the histopathological results.  The overall detection rate was 74 (47 %) PCa cases in 158 included patients. From these 74 PCa cases, 49 (66 %) were graded Gleason ≥ 3 + 4 = 7 (ISUP ≥ 2) PCa. The best results for cancer detection over all quantitative perfusion parameters were rise time (p = 0.026) and time to peak (p = 0.037). Within the subgroup analysis (> vs ≤ 3 + 4 = 7a (ISUP 2)), peak enhancement (p = 0.012), wash-in rate (p = 0.011), wash-out rate (p = 0.007) and wash-in perfusion index (p = 0.014) also showed statistical significance.  The quantification of CEUS parameters was able to discriminate PCa aggressiveness during MRI/US fusion-guided prostate biopsy. © Georg Thieme Verlag KG Stuttgart · New York.

Once upon Multivariate Analyses: When They Tell Several Stories about Biological Evolution.

PubMed

Renaud, Sabrina; Dufour, Anne-Béatrice; Hardouin, Emilie A; Ledevin, Ronan; Auffray, Jean-Christophe

2015-01-01

Geometric morphometrics aims to characterize of the geometry of complex traits. It is therefore by essence multivariate. The most popular methods to investigate patterns of differentiation in this context are (1) the Principal Component Analysis (PCA), which is an eigenvalue decomposition of the total variance-covariance matrix among all specimens; (2) the Canonical Variate Analysis (CVA, a.k.a. linear discriminant analysis (LDA) for more than two groups), which aims at separating the groups by maximizing the between-group to within-group variance ratio; (3) the between-group PCA (bgPCA) which investigates patterns of between-group variation, without standardizing by the within-group variance. Standardizing within-group variance, as performed in the CVA, distorts the relationships among groups, an effect that is particularly strong if the variance is similarly oriented in a comparable way in all groups. Such shared direction of main morphological variance may occur and have a biological meaning, for instance corresponding to the most frequent standing genetic variation in a population. Here we undertake a case study of the evolution of house mouse molar shape across various islands, based on the real dataset and simulations. We investigated how patterns of main variance influence the depiction of among-group differentiation according to the interpretation of the PCA, bgPCA and CVA. Without arguing about a method performing 'better' than another, it rather emerges that working on the total or between-group variance (PCA and bgPCA) will tend to put the focus on the role of direction of main variance as line of least resistance to evolution. Standardizing by the within-group variance (CVA), by dampening the expression of this line of least resistance, has the potential to reveal other relevant patterns of differentiation that may otherwise be blurred.

DCE-MRI of the prostate using shutter-speed vs. Tofts model for tumor characterization and assessment of aggressiveness.

PubMed

Hectors, Stefanie J; Besa, Cecilia; Wagner, Mathilde; Jajamovich, Guido H; Haines, George K; Lewis, Sara; Tewari, Ashutosh; Rastinehad, Ardeshir; Huang, Wei; Taouli, Bachir

2017-09-01

To quantify Tofts model (TM) and shutter-speed model (SSM) perfusion parameters in prostate cancer (PCa) and noncancerous peripheral zone (PZ) and to compare the diagnostic performance of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to Prostate Imaging and Reporting and Data System (PI-RADS) classification for the assessment of PCa aggressiveness. Fifty PCa patients (mean age 60 years old) who underwent MRI at 3.0T followed by prostatectomy were included in this Institutional Review Board-approved retrospective study. DCE-MRI parameters (K trans , v e , k ep [TM&SSM] and intracellular water molecule lifetime τ i [SSM]) were determined in PCa and PZ. Differences in DCE-MRI parameters between PCa and PZ, and between models were assessed using Wilcoxon signed-rank tests. Receiver operating characteristic (ROC) analysis for differentiation between PCa and PZ was performed for individual and combined DCE-MRI parameters. Diagnostic performance of DCE-MRI parameters for identification of aggressive PCa (Gleason ≥8, grade group [GG] ≥3 or pathology stage pT3) was assessed using ROC analysis and compared with PI-RADSv2 scores. DCE-MRI parameters were significantly different between TM and SSM and between PZ and PCa (P < 0.037). Diagnostic performances of TM and SSM for differentiation of PCa from PZ were similar (highest AUC TM: K trans +k ep 0.76, SSM: τ i +k ep 0.80). PI-RADS outperformed TM and SSM DCE-MRI for identification of Gleason ≥8 lesions (AUC PI-RADS: 0.91, highest AUC DCE-MRI: K trans +τ i SSM 0.61, P = 0.002). The diagnostic performance of PI-RADS and DCE-MRI for identification of GG ≥3 and pT3 PCa was not significantly different (P > 0.213). SSM DCE-MRI did not increase the diagnostic performance of DCE-MRI for PCa characterization. PI-RADS outperformed both TM and SSM DCE-MRI for identification of aggressive cancer. 3 Technical Efficacy: Stage 2 J. MAGN. RESON. IMAGING 2017;46:837-849. © 2017 International Society for Magnetic Resonance in Medicine.

Tumor volume in insignificant prostate cancer: increasing threshold gains increasing risk.

PubMed

Schiffmann, Jonas; Connan, Judith; Salomon, Georg; Boehm, Katharina; Beyer, Burkhard; Schlomm, Thorsten; Tennstedt, Pierre; Sauter, Guido; Karakiewicz, Pierre I; Graefen, Markus; Huland, Hartwig

2015-01-01

An increased tumor volume threshold (<2.5 ml) is suggested to define insignificant prostate cancer (iPCa). We hypothesize that an increasing tumor volume within iPCa patients increases the risk of biochemical recurrence (BCR) after radical prostatectomy (RP). We relied on RP patients treated between 1992 and 2008. Multivariable Cox regression analyses predicting BCR within patients harboring favorable pathological characteristics (≤pT2, pN0/Nx, Gleason 3 + 3). Kaplan-Meier analysis was performed for BCR-free survival within iPCa patients (≤pT2, pN0/Nx, Gleason 3 + 3, tumor volume: <0.5 vs. 0.5-2.49 ml). From 1,829 patients, 141 (7.7%) and 310 (16.9%) harbored iPCa (tumor volume: <0.5 vs. 0.5-2.49 ml), respectively. Of those, 21 (14.9%) versus 31 (10.0%) had PSA >10 ng/ml. Tumor volume achieved independent predictor status for BCR. Specifically, iPCa patients with increasing tumor volume (0.5-2.49 ml) were at higher risk of BCR after RP than those with tumor volume <0.5 ml (HR: 8.8, 95% CI: 1.2-65.9, P = 0.04). Kaplan-Meier analysis recorded superior BCR-free survival in iPCa patients with lower tumor volume (<0.5 ml) (log-rank P = 0.009). The 10-year cancer-specific death rate was 0 versus 0.5%. Contemporary iPCa definition incorporates intermediate and high-risk patients (PSA: 10-20 and >20 ng/ml). Despite most favorable pathological characteristics, iPCa patients are not devoid of BCR after RP. Moreover, iPCa patients were at higher risk of BCR, when increasing tumor volume up to 2.49 ml was at play. Taken together the contemporary concept of iPCa is suboptimal. Especially, an increased tumor volume threshold for defining iPCa cannot be recommended according to our data. Clinicians might take these considerations into account during decision-making process. © 2014 Wiley Periodicals, Inc.

Picture agnosia as a characteristic of posterior cortical atrophy.

PubMed

Sugimoto, Azusa; Midorikawa, Akira; Koyama, Shinichi; Futamura, Akinori; Hieda, Sotaro; Kawamura, Mitsuru

2012-01-01

Posterior cortical atrophy (PCA) is a degenerative disease characterized by progressive visual agnosia with posterior cerebral atrophy. We examine the role of the picture naming test and make a number of suggestions with regard to diagnosing PCA as atypical dementia. We investigated 3 cases of early-stage PCA with 7 control cases of Alzheimer disease (AD). The patients and controls underwent a naming test with real objects and colored photographs of familiar objects. We then compared rates of correct answers. Patients with early-stage PCA showed significant inability to recognize photographs compared to real objects (F = 196.284, p = 0.0000) as measured by analysis of variants. This difficulty was also significant to AD controls (F = 58.717, p = 0.0000). Picture agnosia is a characteristic symptom of early-stage PCA, and the picture naming test is useful for the diagnosis of PCA as atypical dementia at an early stage. Copyright © 2012 S. Karger AG, Basel.

Genetic factors influencing prostate cancer risk in Norwegian men.

PubMed

Chen, Haitao; Ewing, Charles M; Zheng, Sigun; Grindedaal, Eli M; Cooney, Kathleen A; Wiley, Kathleen; Djurovic, Srdjan; Andreassen, Ole A; Axcrona, Karol; Mills, Ian G; Xu, Jianfeng; Maehle, Lovise; Fosså, Sophie D; Isaacs, William B

2018-02-01

Norway has one of the highest rates of death due to prostate cancer (PCa) in the world. To assess the contribution of both common and rare single nucleotide variants (SNPs) to the prostate cancer burden in Norway, we assessed the frequency of the established prostate cancer susceptibility allele, HOXB13 G84E, as well as a series of validated, common PCa risk SNPs in a Norwegian PCa population of 779 patients. The G84E allele was observed in 2.3% of patients compared to 0.7% of control individuals, OR = 3.8, P = 1 × 10-4. While there was a trend toward an earlier age at diagnosis, overall the clinicopathologic features of PCa were not significantly different in G84E carriers and non-carriers. Evaluation of 32 established common risk alleles revealed significant associations of risk alleles at 13 loci, including SNPs at 8q24, and near TET2, SLC22A3, NKX3-1, CASC8, MYC, DAP2IP, MSMB, HNF1B, PPP1R14A, and KLK2/3. When the data for each SNP are combined into a genetic risk score (GRS), Norwegian men within the top decile of GRS have over 5-fold greater risk to be diagnosed with PCa than men with GRS in the lowest decile. These results indicate that risk alleles of HOXB13 and common variant SNPs are important components of inherited PCa risk in the Norwegian population, although these factors appear to contribute little to the malignancy's aggressiveness. © 2017 Wiley Periodicals, Inc.

Proton Nuclear Magnetic Resonance-Spectroscopic Discrimination of Wines Reflects Genetic Homology of Several Different Grape (V. vinifera L.) Cultivars

PubMed Central

Zhu, Yong; Wen, Wen; Zhang, Fengmin; Hardie, Jim W.

2015-01-01

Background and Aims Proton nuclear magnetic resonance spectroscopy coupled multivariate analysis (1H NMR-PCA/PLS-DA) is an important tool for the discrimination of wine products. Although 1H NMR has been shown to discriminate wines of different cultivars, a grape genetic component of the discrimination has been inferred only from discrimination of cultivars of undefined genetic homology and in the presence of many confounding environmental factors. We aimed to confirm the influence of grape genotypes in the absence of those factors. Methods and Results We applied 1H NMR-PCA/PLS-DA and hierarchical cluster analysis (HCA) to wines from five, variously genetically-related grapevine (V. vinifera) cultivars; all grown similarly on the same site and vinified similarly. We also compared the semi-quantitative profiles of the discriminant metabolites of each cultivar with previously reported chemical analyses. The cultivars were clearly distinguishable and there was a general correlation between their grouping and their genetic homology as revealed by recent genomic studies. Between cultivars, the relative amounts of several of the cultivar-related discriminant metabolites conformed closely with reported chemical analyses. Conclusions Differences in grape-derived metabolites associated with genetic differences alone are a major source of 1H NMR-based discrimination of wines and 1H NMR has the capacity to discriminate between very closely related cultivars. Significance of the Study The study confirms that genetic variation among grape cultivars alone can account for the discrimination of wine by 1H NMR-PCA/PLS and indicates that 1H NMR spectra of wine of single grape cultivars may in future be used in tandem with hierarchical cluster analysis to elucidate genetic lineages and metabolomic relations of grapevine cultivars. In the absence of genetic information, for example, where predecessor varieties are no longer extant, this may be a particularly useful approach. PMID:26658757

Principal component analysis as a tool for library design: a case study investigating natural products, brand-name drugs, natural product-like libraries, and drug-like libraries.

PubMed

Wenderski, Todd A; Stratton, Christopher F; Bauer, Renato A; Kopp, Felix; Tan, Derek S

2015-01-01

Principal component analysis (PCA) is a useful tool in the design and planning of chemical libraries. PCA can be used to reveal differences in structural and physicochemical parameters between various classes of compounds by displaying them in a convenient graphical format. Herein, we demonstrate the use of PCA to gain insight into structural features that differentiate natural products, synthetic drugs, natural product-like libraries, and drug-like libraries, and show how the results can be used to guide library design.

Principal Component Analysis as a Tool for Library Design: A Case Study Investigating Natural Products, Brand-Name Drugs, Natural Product-Like Libraries, and Drug-Like Libraries

PubMed Central

Wenderski, Todd A.; Stratton, Christopher F.; Bauer, Renato A.; Kopp, Felix; Tan, Derek S.

2015-01-01

Principal component analysis (PCA) is a useful tool in the design and planning of chemical libraries. PCA can be used to reveal differences in structural and physicochemical parameters between various classes of compounds by displaying them in a convenient graphical format. Herein, we demonstrate the use of PCA to gain insight into structural features that differentiate natural products, synthetic drugs, natural product-like libraries, and drug-like libraries, and show how the results can be used to guide library design. PMID:25618349

Spatial assessment of air quality patterns in Malaysia using multivariate analysis

NASA Astrophysics Data System (ADS)

Dominick, Doreena; Juahir, Hafizan; Latif, Mohd Talib; Zain, Sharifuddin M.; Aris, Ahmad Zaharin

2012-12-01

This study aims to investigate possible sources of air pollutants and the spatial patterns within the eight selected Malaysian air monitoring stations based on a two-year database (2008-2009). The multivariate analysis was applied on the dataset. It incorporated Hierarchical Agglomerative Cluster Analysis (HACA) to access the spatial patterns, Principal Component Analysis (PCA) to determine the major sources of the air pollution and Multiple Linear Regression (MLR) to assess the percentage contribution of each air pollutant. The HACA results grouped the eight monitoring stations into three different clusters, based on the characteristics of the air pollutants and meteorological parameters. The PCA analysis showed that the major sources of air pollution were emissions from motor vehicles, aircraft, industries and areas of high population density. The MLR analysis demonstrated that the main pollutant contributing to variability in the Air Pollutant Index (API) at all stations was particulate matter with a diameter of less than 10 μm (PM10). Further MLR analysis showed that the main air pollutant influencing the high concentration of PM10 was carbon monoxide (CO). This was due to combustion processes, particularly originating from motor vehicles. Meteorological factors such as ambient temperature, wind speed and humidity were also noted to influence the concentration of PM10.

Monitoring of an antigen manufacturing process.

PubMed

Zavatti, Vanessa; Budman, Hector; Legge, Raymond; Tamer, Melih

2016-06-01

Fluorescence spectroscopy in combination with multivariate statistical methods was employed as a tool for monitoring the manufacturing process of pertactin (PRN), one of the virulence factors of Bordetella pertussis utilized in whopping cough vaccines. Fluorophores such as amino acids and co-enzymes were detected throughout the process. The fluorescence data collected at different stages of the fermentation and purification process were treated employing principal component analysis (PCA). Through PCA, it was feasible to identify sources of variability in PRN production. Then, partial least square (PLS) was employed to correlate the fluorescence spectra obtained from pure PRN samples and the final protein content measured by a Kjeldahl test from these samples. In view that a statistically significant correlation was found between fluorescence and PRN levels, this approach could be further used as a method to predict the final protein content.

Principal Component Analysis of Thermographic Data

NASA Technical Reports Server (NTRS)

Winfree, William P.; Cramer, K. Elliott; Zalameda, Joseph N.; Howell, Patricia A.; Burke, Eric R.

2015-01-01

Principal Component Analysis (PCA) has been shown effective for reducing thermographic NDE data. While a reliable technique for enhancing the visibility of defects in thermal data, PCA can be computationally intense and time consuming when applied to the large data sets typical in thermography. Additionally, PCA can experience problems when very large defects are present (defects that dominate the field-of-view), since the calculation of the eigenvectors is now governed by the presence of the defect, not the "good" material. To increase the processing speed and to minimize the negative effects of large defects, an alternative method of PCA is being pursued where a fixed set of eigenvectors, generated from an analytic model of the thermal response of the material under examination, is used to process the thermal data from composite materials. This method has been applied for characterization of flaws.

Predictors affecting personal health information management skills.

PubMed

Kim, Sujin; Abner, Erin

2016-01-01

This study investigated major factors affecting personal health records (PHRs) management skills associated with survey respondents' health information management related activities. A self-report survey was used to assess individuals' personal characteristics, health knowledge, PHR skills, and activities. Factors underlying respondents' current PHR-related activities were derived using principal component analysis (PCA). Scale scores were calculated based on the results of the PCA, and hierarchical linear regression analyses were used to identify respondent characteristics associated with the scale scores. Internal consistency of the derived scale scores was assessed with Cronbach's α. Among personal health information activities surveyed (N = 578 respondents), the four extracted factors were subsequently grouped and labeled as: collecting skills (Cronbach's α = 0.906), searching skills (Cronbach's α = 0.837), sharing skills (Cronbach's α = 0.763), and implementing skills (Cronbach's α = 0.908). In the hierarchical regression analyses, education and computer knowledge significantly increased the explanatory power of the models. Health knowledge (β = 0.25, p < 0.001) emerged as a positive predictor of PHR collecting skills. This study confirmed that PHR training and learning should consider a full spectrum of information management skills including collection, utilization and distribution to support patients' care and prevention continua.

Evaluation of skin melanoma in spectral range 450-950 nm using principal component analysis

NASA Astrophysics Data System (ADS)

Jakovels, D.; Lihacova, I.; Kuzmina, I.; Spigulis, J.

2013-06-01

Diagnostic potential of principal component analysis (PCA) of multi-spectral imaging data in the wavelength range 450- 950 nm for distant skin melanoma recognition is discussed. Processing of the measured clinical data by means of PCA resulted in clear separation between malignant melanomas and pigmented nevi.

AlleleCoder: a PERL script for coding codominant polymorphism data for PCA analysis

USDA-ARS?s Scientific Manuscript database

A useful biological interpretation of diploid heterozygotes is in terms of the dose of the common allele (0, 1 or 2 copies). We have developed a PERL script that converts FASTA files into coded spreadsheets suitable for Principal Component Analysis (PCA). In combination with R and R Commander, two- ...

Principle Component Analysis with Incomplete Data: A simulation of R pcaMethods package in Constructing an Environmental Quality Index with Missing Data

EPA Science Inventory

Missing data is a common problem in the application of statistical techniques. In principal component analysis (PCA), a technique for dimensionality reduction, incomplete data points are either discarded or imputed using interpolation methods. Such approaches are less valid when ...

Principal Component Analysis: A Method for Determining the Essential Dynamics of Proteins

PubMed Central

David, Charles C.; Jacobs, Donald J.

2015-01-01

It has become commonplace to employ principal component analysis to reveal the most important motions in proteins. This method is more commonly known by its acronym, PCA. While most popular molecular dynamics packages inevitably provide PCA tools to analyze protein trajectories, researchers often make inferences of their results without having insight into how to make interpretations, and they are often unaware of limitations and generalizations of such analysis. Here we review best practices for applying standard PCA, describe useful variants, discuss why one may wish to make comparison studies, and describe a set of metrics that make comparisons possible. In practice, one will be forced to make inferences about the essential dynamics of a protein without having the desired amount of samples. Therefore, considerable time is spent on describing how to judge the significance of results, highlighting pitfalls. The topic of PCA is reviewed from the perspective of many practical considerations, and useful recipes are provided. PMID:24061923

Principal component analysis: a method for determining the essential dynamics of proteins.

PubMed

David, Charles C; Jacobs, Donald J

2014-01-01

It has become commonplace to employ principal component analysis to reveal the most important motions in proteins. This method is more commonly known by its acronym, PCA. While most popular molecular dynamics packages inevitably provide PCA tools to analyze protein trajectories, researchers often make inferences of their results without having insight into how to make interpretations, and they are often unaware of limitations and generalizations of such analysis. Here we review best practices for applying standard PCA, describe useful variants, discuss why one may wish to make comparison studies, and describe a set of metrics that make comparisons possible. In practice, one will be forced to make inferences about the essential dynamics of a protein without having the desired amount of samples. Therefore, considerable time is spent on describing how to judge the significance of results, highlighting pitfalls. The topic of PCA is reviewed from the perspective of many practical considerations, and useful recipes are provided.

Incidental prostate cancer in patients with muscle-invasive bladder cancer who underwent radical cystoprostatectomy.

PubMed

Tanaka, Toshikazu; Koie, Takuya; Ohyama, Chikara; Hashimoto, Yasuhiro; Imai, Atsushi; Tobisawa, Yuki; Hatakeyama, Shingo; Yamamoto, Hayato; Yoneyama, Tohru; Horiguchi, Hirotaka; Kodama, Hirotake; Yoneyama, Takahiro

2017-11-01

The aim of this study was to analyze the features of incidentally detected prostate cancer (PCa) in radical cystoprostatectomy (RCP) specimens to determine their pathological characteristics and clinical significance. In this retrospective study, we reviewed the clinical and pathological records of 431 consecutive patients with muscle-invasive bladder cancer who underwent RCP at Hirosaki University. Of these, we focused on 237 male patients with prostate-specific antigen (PSA) measurements and digital rectal examinations (DRE) that were recorded prior to the RCP. Significant PCa was defined as a tumor with a Gleason 4 or 5 pattern, pathological T3 or higher stage, lymph node involvement or three or more multifocal lesions within the prostate specimen. We compared clinically significant and insignificant PCa. In this study, a total of 43 patients (18.1%) were diagnosed with incidental PCa via RCP specimens. Age, preoperative PSA levels and pathological T stage in patients with clinically significant PCa were considerably higher than in those with insignificant cancer. Apical involvement was found in 16 patients, including 11 of those with clinically significant PCa. By the end of the follow-up period, none of the enrolled patients had a biochemical recurrence after surgery or died from PCa. According to our findings, preoperative risk factors were not reliable enough to accurately predict clinically significant PCa. Although there was no biochemical relapse or clinical recurrence of PCa in this study, the potential oncologic risk of prostate-sparing RCP must be considered. © The Author 2017. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Characterization of Argentine honeys on the basis of their mineral content and some typical quality parameters

PubMed Central

2014-01-01

Background The levels of 19 elements (As, Be, Ca, Cd, Co, Cr, Cu, Fe, K, Mg, Mn, Na, Ni, Pb, Se, Tl, U, V, Zn) from sixteen different Argentine production sites of unifloral [eucalyptus (Eucaliptus rostrata), chilca (Baccharis salicifolia), Algarrobo (Prosopis sp.), mistol (Ziziphus mistol) and citric] and multifloral honeys were measured with the aim to test the quality of the selected samples. Typical quality parameters of honeys were also determined (pH, sugar content, moisture). Mineral elements were determined by using inductively coupled plasma mass spectrometer (ICP-MS DRC). We also evaluated the suitability of honey as a possible biomonitor of environmental pollution. Thus, the sites were classified through cluster analysis (CA) and then pattern recognition methods such as Principal Component Analysis (PCA) and discriminant analysis (DA) were applied. Results Mean values for quality parameters were: pH, 4.12 and 3.81; sugar 82.1 and 82.0 °brix; moisture, 16.90 and 17.00% for unifloral and multifloral honeys respectively. The water content showed good maturity. Likewise, the other parameters confirmed the good quality of the honeys analysed. Potassium was quantitatively the most abundant metal, accounting for 92,5% of the total metal contents with an average concentration of 832.0 and 816.2 μg g-1 for unifloral and multifloral honeys respectively. Sodium was the second most abundant major metal in honeys with a mean value of 32.16 and 33.19 μg g-1 for unifloral and multifloral honeys respectively. Mg, Ca, Fe, Mn, Zn and Cu were present at low-intermediate concentrations. For the other 11 trace elements determined in this study (As, Be, Cd, Co, Cr, Ni, Pb, Se, Tl, U and V), the mean concentrations were very low or below of the LODs. The sites were classified through CA by using elements’ and physicochemical parameters data, then DA on the PCA factors was applied. Dendrograms identified three main groups. PCA explained 52.03% of the total variability with the first two factors. Conclusions In general, there are no evidences of pollution for the analysed honeys. The analytical results obtained for the Argentine honeys indicate the products’ high quality. In fact, most of the toxic elements were below LODs. The chemometric analysis combining CA, DA and PCA showed their aptness as useful tools for honey’s classification. Eventually, this study confirms that the use of honey as biomonitor of environmental contamination is not reliable for sites with low levels of contamination. PMID:25057287

Approximate probabilistic cellular automata for the dynamics of single-species populations under discrete logisticlike growth with and without weak Allee effects.

PubMed

Mendonça, J Ricardo G; Gevorgyan, Yeva

2017-05-01

We investigate one-dimensional elementary probabilistic cellular automata (PCA) whose dynamics in first-order mean-field approximation yields discrete logisticlike growth models for a single-species unstructured population with nonoverlapping generations. Beginning with a general six-parameter model, we find constraints on the transition probabilities of the PCA that guarantee that the ensuing approximations make sense in terms of population dynamics and classify the valid combinations thereof. Several possible models display a negative cubic term that can be interpreted as a weak Allee factor. We also investigate the conditions under which a one-parameter PCA derived from the more general six-parameter model can generate valid population growth dynamics. Numerical simulations illustrate the behavior of some of the PCA found.

Virtual reality as a human factors design analysis tool: Macro-ergonomic application validation and assessment of the Space Station Freedom payload control area

NASA Technical Reports Server (NTRS)

Hale, Joseph P.

1994-01-01

A virtual reality (VR) Applications Program has been under development at MSFC since 1989. Its objectives are to develop, assess, validate, and utilize VR in hardware development, operations development and support, missions operations training, and science training. A variety of activities are under way within many of these areas. One ongoing macro-ergonomic application of VR relates to the design of the Space Station Freedom Payload Control Area (PCA), the control room from which onboard payload operations are managed. Several preliminary conceptual PCA layouts have been developed and modeled in VR. Various managers and potential end users have virtually 'entered' these rooms and provided valuable feedback. Before VR can be used with confidence in a particular application, it must be validated, or calibrated, for that class of applications. Two associated validation studies for macro-ergonomic applications are under way to help characterize possible distortions of filtering of relevant perceptions in a virtual world. In both studies, existing control rooms and their 'virtual counterparts will be empirically compared using distance and heading estimations to objects and subjective assessments. Approaches and findings of the PCA activities and details of the studies are presented.

ICI 182,780-regulated gene expression in DU145 prostate cancer cells is mediated by estrogen receptor-beta/NFkappaB crosstalk.

PubMed

Leung, Yuet-Kin; Gao, Ying; Lau, Kin-Mang; Zhang, Xiang; Ho, Shuk-Mei

2006-04-01

Estrogen receptor (ER)-beta is the predominant ER subtype in prostate cancer (PCa). We previously demonstrated that ICI 182,780 (ICI), but not estrogens, exerted dose-dependent growth inhibition on DU145 PCa cells by an ER-beta-mediated pathway. Transcriptional profiling detected a greater than three-fold upregulation of seven genes after a 12-hour exposure to 1 microM ICI. Semiquantitative reverse transcriptase polymerase chain reaction confirmed the upregulation of four genes by ICI: interleukin-12alpha chain, interleukin-8, embryonic growth/differentiation factor, and RYK tyrosine kinase. Treatment with an ER-beta antisense oligonucleotide reduced cellular ER-beta mRNA and induced loss of expression of these genes. Sequence analysis revealed the presence of consensus NFkappaB sites, but not estrogen-responsive elements, in promoters of all four genes. Reporter assay and chromatin immunoprecipitation experiments demonstrated that ICI-induced gene expression could be mediated by crosstalk between ER-beta and the NFkappaB signaling pathway, denoting a novel mechanism of ER-beta-mediated ICI action. Therefore, combined therapies targeting ER-beta and NFkappaB signaling may be synergistic as treatment for PCa.

ICI 182,780-Regulated Gene Expression in DU145 Prostate Cancer Cells Is Mediated by Estrogen Receptor-β/NFκB Crosstalk1

PubMed Central

Leung, Yuet-Kin; Gao, Ying; Lau, Kin-Mang; Zhang, Xiang; Ho, Shuk-Mei

2006-01-01

Abstract Estrogen receptor (ER)-β is the predominant ER subtype in prostate cancer (PCa). We previously demonstrated that ICI 182,780 (ICI), but not estrogens, exerted dose-dependent growth inhibition on DU145 PCa cells by an ER-β-mediated pathway. Transcriptional profiling detected a greater than three-fold upregulation of seven genes after a 12-hour exposure to 1 µM ICI. Semi-quantitative reverse transcriptase polymerase chain reaction confirmed the upregulation of four genes by ICI: interleukin-12α chain, interleukin-8, embryonic growth/differentiation factor, and RYK tyrosine kinase. Treatment with an ER-β antisense oligonucleotide reduced cellular ER-β mRNA and induced loss of expression of these genes. Sequence analysis revealed the presence of consensus NFκB sites, but not estrogen-responsive elements, in promoters of all four genes. Reporter assay and chromatin immunoprecipitation experiments demonstrated that ICI-induced gene expression could be mediated by crosstalk between ER-α and the NFκB signaling pathway, denoting a novel mechanism of ER-β-mediated ICI action. Therefore, combined therapies targeting ER-β and NFκB signaling may be synergistic as treatment for PCa. PMID:16756716

On a PCA-based lung motion model

PubMed Central

Li, Ruijiang; Lewis, John H; Jia, Xun; Zhao, Tianyu; Liu, Weifeng; Wuenschel, Sara; Lamb, James; Yang, Deshan; Low, Daniel A; Jiang, Steve B

2014-01-01

Respiration-induced organ motion is one of the major uncertainties in lung cancer radiotherapy and is crucial to be able to accurately model the lung motion. Most work so far has focused on the study of the motion of a single point (usually the tumor center of mass), and much less work has been done to model the motion of the entire lung. Inspired by the work of Zhang et al (2007 Med. Phys. 34 4772–81), we believe that the spatiotemporal relationship of the entire lung motion can be accurately modeled based on principle component analysis (PCA) and then a sparse subset of the entire lung, such as an implanted marker, can be used to drive the motion of the entire lung (including the tumor). The goal of this work is twofold. First, we aim to understand the underlying reason why PCA is effective for modeling lung motion and find the optimal number of PCA coefficients for accurate lung motion modeling. We attempt to address the above important problems both in a theoretical framework and in the context of real clinical data. Second, we propose a new method to derive the entire lung motion using a single internal marker based on the PCA model. The main results of this work are as follows. We derived an important property which reveals the implicit regularization imposed by the PCA model. We then studied the model using two mathematical respiratory phantoms and 11 clinical 4DCT scans for eight lung cancer patients. For the mathematical phantoms with cosine and an even power (2n) of cosine motion, we proved that 2 and 2n PCA coefficients and eigenvectors will completely represent the lung motion, respectively. Moreover, for the cosine phantom, we derived the equivalence conditions for the PCA motion model and the physiological 5D lung motion model (Low et al 2005 Int. J. Radiat. Oncol. Biol. Phys. 63 921–9). For the clinical 4DCT data, we demonstrated the modeling power and generalization performance of the PCA model. The average 3D modeling error using PCA was within 1 mm (0.7 ± 0.1 mm). When a single artificial internal marker was used to derive the lung motion, the average 3D error was found to be within 2 mm (1.8 ± 0.3 mm) through comprehensive statistical analysis. The optimal number of PCA coefficients needs to be determined on a patient-by-patient basis and two PCA coefficients seem to be sufficient for accurate modeling of the lung motion for most patients. In conclusion, we have presented thorough theoretical analysis and clinical validation of the PCA lung motion model. The feasibility of deriving the entire lung motion using a single marker has also been demonstrated on clinical data using a simulation approach. PMID:21865624

An exploratory risk perception study of attitudes toward homeland security systems.

PubMed

Sanquist, Thomas F; Mahy, Heidi; Morris, Frederic

2008-08-01

Understanding the issues surrounding public acceptance of homeland security systems is important for balancing security needs and potential civil liberties infringements. A psychometric survey was used in an exploratory study of attitudes regarding homeland security systems. Psychometric rating data were obtained from 182 respondents on psychological attributes associated with 12 distinct types of homeland security systems. An inverse relationship was observed for the overall rating attributes of acceptability and risk of civil liberties infringement. Principal components analysis (PCA) yielded a two-factor solution with the rating scale loading pattern suggesting factors of perceived effectiveness and perceived intrusiveness. These factors also showed an inverse relationship. The 12 different homeland security systems showed significantly different scores on the rating scales and PCA factors. Of the 12 systems studied, airport screening, canine detectors, and radiation monitoring at borders were found to be the most acceptable, while email monitoring, data mining, and global positioning satellite (GPS) tracking were found to be least acceptable. Students rated several systems as more effective than professionals, but the overall pattern of results for both types of subjects was similar. The data suggest that risk perception research and the psychometric paradigm are useful approaches for quantifying attitudes regarding homeland security systems and policies and can be used to anticipate potentially significant public acceptance issues.

Population Analysis of Disabled Children by Departments in France

NASA Astrophysics Data System (ADS)

Meidatuzzahra, Diah; Kuswanto, Heri; Pech, Nicolas; Etchegaray, Amélie

2017-06-01

In this study, a statistical analysis is performed by model the variations of the disabled about 0-19 years old population among French departments. The aim is to classify the departments according to their profile determinants (socioeconomic and behavioural profiles). The analysis is focused on two types of methods: principal component analysis (PCA) and multiple correspondences factorial analysis (MCA) to review which one is the best methods for interpretation of the correlation between the determinants of disability (independent variable). The PCA is the best method for interpretation of the correlation between the determinants of disability (independent variable). The PCA reduces 14 determinants of disability to 4 axes, keeps 80% of total information, and classifies them into 7 classes. The MCA reduces the determinants to 3 axes, retains only 30% of information, and classifies them into 4 classes.

Examining the factor structure of MUIS-C scale among baby boomers with hepatitis C.

PubMed

Reinoso, Humberto; Türegün, Mehmet

2016-11-01

Baby boomers account for two out of every three cases of hepatitis C infection in the U.S. To conduct an exploratory factor analysis directed at supporting the use of the MUIS-C as a reliable instrument in measuring illness uncertainty among baby boomers with hepatitis C. The steps of conducting a typical principal component analysis (PCA) with an oblique rotation were used on a sample of 146 participants, the sampling adequacy of items was examined via the Kaiser-Meyer-Olkin (KMO) measure, and the Bartlett's sphericity test was used for appropriateness of conducting a factor analysis. A two-factor structure was obtained by using Horn's parallel analysis method. The two factors explained a cumulative total of 45.8% of the variance. The results of the analyses indicated that the MUIS-C was a valid and reliable instrument and potentially suitable for use in baby boomer population diagnosed with hepatitis C. Published by Elsevier Inc.

Suicide ideation and attempt in a community cohort of urban Aboriginal youth: a cross-sectional study.

PubMed

Luke, Joanne N; Anderson, Ian P; Gee, Graham J; Thorpe, Reg; Rowley, Kevin G; Reilly, Rachel E; Thorpe, Alister; Stewart, Paul J

2013-01-01

There has been increasing attention over the last decade on the issue of indigenous youth suicide. A number of studies have documented the high prevalence of suicide behavior and mortality in Australia and internationally. However, no studies have focused on documenting the correlates of suicide behavior for indigenous youth in Australia. To examine the prevalence of suicide ideation and attempt and the associated factors for a community1 cohort of Koori2 (Aboriginal) youth. Data were obtained from the Victorian Aboriginal Health Service (VAHS) Young People's Project (YPP), a community initiated cross-sectional data set. In 1997/1998, self-reported data were collected for 172 Koori youth aged 12-26 years living in Melbourne, Australia. The data were analyzed to assess the prevalence of current suicide ideation and lifetime suicide attempt. Principal components analysis (PCA) was used to identify closely associated social, emotional, behavioral, and cultural variables at baseline and Cox regression modeling was then used to identify associations between PCA components and suicide ideation and attempt. Ideation and attempt were reported at 23.3% and 24.4%, respectively. PCA yielded five components: (1) emotional distress, (2) social distress A, (3) social distress B, (4) cultural connection, (5) behavioral. All were positively and independently associated with suicide ideation and attempt, while cultural connection showed a negative association. Suicide ideation and attempt were common in this cross-section of indigenous youth with an unfavorable profile for the emotional, social, cultural, and behavioral factors.

Prediction of ozone concentration in tropospheric levels using artificial neural networks and support vector machine at Rio de Janeiro, Brazil

NASA Astrophysics Data System (ADS)

Luna, A. S.; Paredes, M. L. L.; de Oliveira, G. C. G.; Corrêa, S. M.

2014-12-01

It is well known that air quality is a complex function of emissions, meteorology and topography, and statistical tools provide a sound framework for relating these variables. The observed data were contents of nitrogen dioxide (NO2), nitrogen monoxide (NO), nitrogen oxides (NOx), carbon monoxide (CO), ozone (O3), scalar wind speed (SWS), global solar radiation (GSR), temperature (TEM), moisture content in the air (HUM), collected by a mobile automatic monitoring station at Rio de Janeiro City in two places of the metropolitan area during 2011 and 2012. The aims of this study were: (1) to analyze the behavior of the variables, using the method of PCA for exploratory data analysis; (2) to propose forecasts of O3 levels from primary pollutants and meteorological factors, using nonlinear regression methods like ANN and SVM, from primary pollutants and meteorological factors. The PCA technique showed that for first dataset, variables NO, NOx and SWS have a greater impact on the concentration of O3 and the other data set had the TEM and GSR as the most influential variables. The obtained results from the nonlinear regression techniques ANN and SVM were remarkably closely and acceptable to one dataset presenting coefficient of determination for validation respectively 0.9122 and 0.9152, and root mean square error of 7.66 and 7.85, respectively. For these datasets, the PCA, SVM and ANN had demonstrated their robustness as useful tools for evaluation, and forecast scenarios for air quality.

Indirect Field Measurement of Wine-Grape Vineyard Canopy Leaf Area Index

NASA Technical Reports Server (NTRS)

Johnson, Lee F.; Pierce, Lars L.; Skiles, J. W. (Technical Monitor)

2002-01-01

Leaf area index (LAI) indirect measurements were made at 12 study plots in California's Napa Valley commercial wine-grape vineyards with a LI-COR LI-2000 Plant Canopy Analyzer (PCA). The plots encompassed different trellis systems, biological varieties, and planting densities. LAI ranged from 0.5 - 2.25 sq m leaf area/ sq m ground area according to direct (defoliation) measurements. Indirect LAI reported by the PCA was significantly related to direct LAI (r(exp 2) = 0.78, p less than 001). However, the PCA tended to underestimate direct LAI by about a factor of two. Narrowing the instrument's conical field of view from 148 deg to 56 deg served to increase readings by approximately 30%. The PCA offers a convenient way to discern relative differences in vineyard canopy density. Calibration by direct measurement (defoliation) is recommended in cases where absolute LAI is desired. Calibration equations provided herein may be inverted to retrieve actual vineyard LAI from PCA readings.

Prostate Cancer Cell–Stromal Cell Cross-Talk via FGFR1 Mediates Antitumor Activity of Dovitinib in Bone Metastases

PubMed Central

Wan, Xinhai; Corn, Paul G.; Yang, Jun; Palanisamy, Nallasivam; Starbuck, Michael W.; Efstathiou, Eleni; Li-Ning Tapia, Elsa M.; Zurita, Amado J.; Aparicio, Ana; Ravoori, Murali K.; Vazquez, Elba S.; Robinson, Dan R.; Wu, Yi-Mi; Cao, Xuhong; Iyer, Matthew K.; McKeehan, Wallace; Kundra, Vikas; Wang, Fen; Troncoso, Patricia; Chinnaiyan, Arul M.; Logothetis, Christopher J.; Navone, Nora M.

2015-01-01

Bone is the most common site of prostate cancer (PCa) progression to a therapy-resistant, lethal phenotype. We found that blockade of fibroblast growth factor receptors (FGFRs) with the receptor tyrosine kinase inhibitor dovitinib has clinical activity in a subset of men with castration-resistant PCa and bone metastases. Our integrated analyses suggest that FGF signaling mediates a positive feedback loop between PCa cells and bone cells and that blockade of FGFR1 in osteoblasts partially mediates the antitumor activity of dovitinib by improving bone quality and by blocking PCa cell–bone cell interaction. These findings account for clinical observations such as reductions in lesion size and intensity on bone scans, lymph node size, and tumor-specific symptoms without proportional declines in prostate-specific antigen concentration. Our findings suggest that targeting FGFR has therapeutic activity in advanced PCa and provide direction for the development of therapies with FGFR inhibitors. PMID:25186177

Prostate cancer cell-stromal cell crosstalk via FGFR1 mediates antitumor activity of dovitinib in bone metastases.

PubMed

Wan, Xinhai; Corn, Paul G; Yang, Jun; Palanisamy, Nallasivam; Starbuck, Michael W; Efstathiou, Eleni; Li Ning Tapia, Elsa M; Tapia, Elsa M Li-Ning; Zurita, Amado J; Aparicio, Ana; Ravoori, Murali K; Vazquez, Elba S; Robinson, Dan R; Wu, Yi-Mi; Cao, Xuhong; Iyer, Matthew K; McKeehan, Wallace; Kundra, Vikas; Wang, Fen; Troncoso, Patricia; Chinnaiyan, Arul M; Logothetis, Christopher J; Navone, Nora M

2014-09-03

Bone is the most common site of prostate cancer (PCa) progression to a therapy-resistant, lethal phenotype. We found that blockade of fibroblast growth factor receptors (FGFRs) with the receptor tyrosine kinase inhibitor dovitinib has clinical activity in a subset of men with castration-resistant PCa and bone metastases. Our integrated analyses suggest that FGF signaling mediates a positive feedback loop between PCa cells and bone cells and that blockade of FGFR1 in osteoblasts partially mediates the antitumor activity of dovitinib by improving bone quality and by blocking PCa cell-bone cell interaction. These findings account for clinical observations such as reductions in lesion size and intensity on bone scans, lymph node size, and tumor-specific symptoms without proportional declines in serum prostate-specific antigen concentration. Our findings suggest that targeting FGFR has therapeutic activity in advanced PCa and provide direction for the development of therapies with FGFR inhibitors. Copyright © 2014, American Association for the Advancement of Science.

Prostate Health Index (Phi) and Prostate Cancer Antigen 3 (PCA3) Significantly Improve Prostate Cancer Detection at Initial Biopsy in a Total PSA Range of 2–10 ng/ml

PubMed Central

Perdonà, Sisto; Marino, Ada; Mazzarella, Claudia; Perruolo, Giuseppe; D’Esposito, Vittoria; Cosimato, Vincenzo; Buonerba, Carlo; Di Lorenzo, Giuseppe; Musi, Gennaro; De Cobelli, Ottavio; Chun, Felix K.; Terracciano, Daniela

2013-01-01

Many efforts to reduce prostate specific antigen (PSA) overdiagnosis and overtreatment have been made. To this aim, Prostate Health Index (Phi) and Prostate Cancer Antigen 3 (PCA3) have been proposed as new more specific biomarkers. We evaluated the ability of phi and PCA3 to identify prostate cancer (PCa) at initial prostate biopsy in men with total PSA range of 2–10 ng/ml. The performance of phi and PCA3 were evaluated in 300 patients undergoing first prostate biopsy. ROC curve analyses tested the accuracy (AUC) of phi and PCA3 in predicting PCa. Decision curve analyses (DCA) were used to compare the clinical benefit of the two biomarkers. We found that the AUC value of phi (0.77) was comparable to those of %p2PSA (0.76) and PCA3 (0.73) with no significant differences in pairwise comparison (%p2PSA vs phi p = 0.673, %p2PSA vs. PCA3 p = 0.417 and phi vs. PCA3 p = 0.247). These three biomarkers significantly outperformed fPSA (AUC = 0.60), % fPSA (AUC = 0.62) and p2PSA (AUC = 0.63). At DCA, phi and PCA3 exhibited a very close net benefit profile until the threshold probability of 25%, then phi index showed higher net benefit than PCA3. Multivariable analysis showed that the addition of phi and PCA3 to the base multivariable model (age, PSA, %fPSA, DRE, prostate volume) increased predictive accuracy, whereas no model improved single biomarker performance. Finally we showed that subjects with active surveillance (AS) compatible cancer had significantly lower phi and PCA3 values (p<0.001 and p = 0.01, respectively). In conclusion, both phi and PCA3 comparably increase the accuracy in predicting the presence of PCa in total PSA range 2–10 ng/ml at initial biopsy, outperforming currently used %fPSA. PMID:23861782

Prostate Health Index (Phi) and Prostate Cancer Antigen 3 (PCA3) significantly improve prostate cancer detection at initial biopsy in a total PSA range of 2-10 ng/ml.

PubMed

Ferro, Matteo; Bruzzese, Dario; Perdonà, Sisto; Marino, Ada; Mazzarella, Claudia; Perruolo, Giuseppe; D'Esposito, Vittoria; Cosimato, Vincenzo; Buonerba, Carlo; Di Lorenzo, Giuseppe; Musi, Gennaro; De Cobelli, Ottavio; Chun, Felix K; Terracciano, Daniela

2013-01-01

Many efforts to reduce prostate specific antigen (PSA) overdiagnosis and overtreatment have been made. To this aim, Prostate Health Index (Phi) and Prostate Cancer Antigen 3 (PCA3) have been proposed as new more specific biomarkers. We evaluated the ability of phi and PCA3 to identify prostate cancer (PCa) at initial prostate biopsy in men with total PSA range of 2-10 ng/ml. The performance of phi and PCA3 were evaluated in 300 patients undergoing first prostate biopsy. ROC curve analyses tested the accuracy (AUC) of phi and PCA3 in predicting PCa. Decision curve analyses (DCA) were used to compare the clinical benefit of the two biomarkers. We found that the AUC value of phi (0.77) was comparable to those of %p2PSA (0.76) and PCA3 (0.73) with no significant differences in pairwise comparison (%p2PSA vs phi p = 0.673, %p2PSA vs. PCA3 p = 0.417 and phi vs. PCA3 p = 0.247). These three biomarkers significantly outperformed fPSA (AUC = 0.60), % fPSA (AUC = 0.62) and p2PSA (AUC = 0.63). At DCA, phi and PCA3 exhibited a very close net benefit profile until the threshold probability of 25%, then phi index showed higher net benefit than PCA3. Multivariable analysis showed that the addition of phi and PCA3 to the base multivariable model (age, PSA, %fPSA, DRE, prostate volume) increased predictive accuracy, whereas no model improved single biomarker performance. Finally we showed that subjects with active surveillance (AS) compatible cancer had significantly lower phi and PCA3 values (p<0.001 and p = 0.01, respectively). In conclusion, both phi and PCA3 comparably increase the accuracy in predicting the presence of PCa in total PSA range 2-10 ng/ml at initial biopsy, outperforming currently used %fPSA.

A Seven-Gene Locus for Synthesis of Phenazine-1-Carboxylic Acid by Pseudomonas fluorescens 2-79

PubMed Central

Mavrodi, Dmitri V.; Ksenzenko, Vladimir N.; Bonsall, Robert F.; Cook, R. James; Boronin, Alexander M.; Thomashow, Linda S.

1998-01-01

Pseudomonas fluorescens 2-79 produces the broad-spectrum antibiotic phenazine-1-carboxylic acid (PCA), which is active against a variety of fungal root pathogens. In this study, seven genes designated phzABCDEFG that are sufficient for synthesis of PCA were localized within a 6.8-kb BglII-XbaI fragment from the phenazine biosynthesis locus of strain 2-79. Polypeptides corresponding to all phz genes were identified by analysis of recombinant plasmids in a T7 promoter/polymerase expression system. Products of the phzC, phzD, and phzE genes have similarities to enzymes of shikimic acid and chorismic acid metabolism and, together with PhzF, are absolutely necessary for PCA production. PhzG is similar to pyridoxamine-5′-phosphate oxidases and probably is a source of cofactor for the PCA-synthesizing enzyme(s). Products of the phzA and phzB genes are highly homologous to each other and may be involved in stabilization of a putative PCA-synthesizing multienzyme complex. Two new genes, phzX and phzY, that are homologous to phzA and phzB, respectively, were cloned and sequenced from P. aureofaciens 30-84, which produces PCA, 2-hydroxyphenazine-1-carboxylic acid, and 2-hydroxyphenazine. Based on functional analysis of the phz genes from strains 2-79 and 30-84, we postulate that different species of fluorescent pseudomonads have similar genetic systems that confer the ability to synthesize PCA. PMID:9573209

VIP: Vortex Image Processing Package for High-contrast Direct Imaging

NASA Astrophysics Data System (ADS)

Gomez Gonzalez, Carlos Alberto; Wertz, Olivier; Absil, Olivier; Christiaens, Valentin; Defrère, Denis; Mawet, Dimitri; Milli, Julien; Absil, Pierre-Antoine; Van Droogenbroeck, Marc; Cantalloube, Faustine; Hinz, Philip M.; Skemer, Andrew J.; Karlsson, Mikael; Surdej, Jean

2017-07-01

We present the Vortex Image Processing (VIP) library, a python package dedicated to astronomical high-contrast imaging. Our package relies on the extensive python stack of scientific libraries and aims to provide a flexible framework for high-contrast data and image processing. In this paper, we describe the capabilities of VIP related to processing image sequences acquired using the angular differential imaging (ADI) observing technique. VIP implements functionalities for building high-contrast data processing pipelines, encompassing pre- and post-processing algorithms, potential source position and flux estimation, and sensitivity curve generation. Among the reference point-spread function subtraction techniques for ADI post-processing, VIP includes several flavors of principal component analysis (PCA) based algorithms, such as annular PCA and incremental PCA algorithms capable of processing big datacubes (of several gigabytes) on a computer with limited memory. Also, we present a novel ADI algorithm based on non-negative matrix factorization, which comes from the same family of low-rank matrix approximations as PCA and provides fairly similar results. We showcase the ADI capabilities of the VIP library using a deep sequence on HR 8799 taken with the LBTI/LMIRCam and its recently commissioned L-band vortex coronagraph. Using VIP, we investigated the presence of additional companions around HR 8799 and did not find any significant additional point source beyond the four known planets. VIP is available at http://github.com/vortex-exoplanet/VIP and is accompanied with Jupyter notebook tutorials illustrating the main functionalities of the library.

Facilitating Neuronal Connectivity Analysis of Evoked Responses by Exposing Local Activity with Principal Component Analysis Preprocessing: Simulation of Evoked MEG

PubMed Central

Gao, Lin; Zhang, Tongsheng; Wang, Jue; Stephen, Julia

2014-01-01

When connectivity analysis is carried out for event related EEG and MEG, the presence of strong spatial correlations from spontaneous activity in background may mask the local neuronal evoked activity and lead to spurious connections. In this paper, we hypothesized PCA decomposition could be used to diminish the background activity and further improve the performance of connectivity analysis in event related experiments. The idea was tested using simulation, where we found that for the 306-channel Elekta Neuromag system, the first 4 PCs represent the dominant background activity, and the source connectivity pattern after preprocessing is consistent with the true connectivity pattern designed in the simulation. Improving signal to noise of the evoked responses by discarding the first few PCs demonstrates increased coherences at major physiological frequency bands when removing the first few PCs. Furthermore, the evoked information was maintained after PCA preprocessing. In conclusion, it is demonstrated that the first few PCs represent background activity, and PCA decomposition can be employed to remove it to expose the evoked activity for the channels under investigation. Therefore, PCA can be applied as a preprocessing approach to improve neuronal connectivity analysis for event related data. PMID:22918837

Facilitating neuronal connectivity analysis of evoked responses by exposing local activity with principal component analysis preprocessing: simulation of evoked MEG.

PubMed

Gao, Lin; Zhang, Tongsheng; Wang, Jue; Stephen, Julia

2013-04-01

When connectivity analysis is carried out for event related EEG and MEG, the presence of strong spatial correlations from spontaneous activity in background may mask the local neuronal evoked activity and lead to spurious connections. In this paper, we hypothesized PCA decomposition could be used to diminish the background activity and further improve the performance of connectivity analysis in event related experiments. The idea was tested using simulation, where we found that for the 306-channel Elekta Neuromag system, the first 4 PCs represent the dominant background activity, and the source connectivity pattern after preprocessing is consistent with the true connectivity pattern designed in the simulation. Improving signal to noise of the evoked responses by discarding the first few PCs demonstrates increased coherences at major physiological frequency bands when removing the first few PCs. Furthermore, the evoked information was maintained after PCA preprocessing. In conclusion, it is demonstrated that the first few PCs represent background activity, and PCA decomposition can be employed to remove it to expose the evoked activity for the channels under investigation. Therefore, PCA can be applied as a preprocessing approach to improve neuronal connectivity analysis for event related data.

An Intelligent Architecture Based on Field Programmable Gate Arrays Designed to Detect Moving Objects by Using Principal Component Analysis

PubMed Central

Bravo, Ignacio; Mazo, Manuel; Lázaro, José L.; Gardel, Alfredo; Jiménez, Pedro; Pizarro, Daniel

2010-01-01

This paper presents a complete implementation of the Principal Component Analysis (PCA) algorithm in Field Programmable Gate Array (FPGA) devices applied to high rate background segmentation of images. The classical sequential execution of different parts of the PCA algorithm has been parallelized. This parallelization has led to the specific development and implementation in hardware of the different stages of PCA, such as computation of the correlation matrix, matrix diagonalization using the Jacobi method and subspace projections of images. On the application side, the paper presents a motion detection algorithm, also entirely implemented on the FPGA, and based on the developed PCA core. This consists of dynamically thresholding the differences between the input image and the one obtained by expressing the input image using the PCA linear subspace previously obtained as a background model. The proposal achieves a high ratio of processed images (up to 120 frames per second) and high quality segmentation results, with a completely embedded and reliable hardware architecture based on commercial CMOS sensors and FPGA devices. PMID:22163406

An intelligent architecture based on Field Programmable Gate Arrays designed to detect moving objects by using Principal Component Analysis.

PubMed

Bravo, Ignacio; Mazo, Manuel; Lázaro, José L; Gardel, Alfredo; Jiménez, Pedro; Pizarro, Daniel

2010-01-01

This paper presents a complete implementation of the Principal Component Analysis (PCA) algorithm in Field Programmable Gate Array (FPGA) devices applied to high rate background segmentation of images. The classical sequential execution of different parts of the PCA algorithm has been parallelized. This parallelization has led to the specific development and implementation in hardware of the different stages of PCA, such as computation of the correlation matrix, matrix diagonalization using the Jacobi method and subspace projections of images. On the application side, the paper presents a motion detection algorithm, also entirely implemented on the FPGA, and based on the developed PCA core. This consists of dynamically thresholding the differences between the input image and the one obtained by expressing the input image using the PCA linear subspace previously obtained as a background model. The proposal achieves a high ratio of processed images (up to 120 frames per second) and high quality segmentation results, with a completely embedded and reliable hardware architecture based on commercial CMOS sensors and FPGA devices.

Silibinin inhibits prostate cancer cells- and RANKL-induced osteoclastogenesis by targeting NFATc1, NF-κB, and AP-1 activation in RAW264.7 cells.

PubMed

Kavitha, Chandagirikoppal V; Deep, Gagan; Gangar, Subhash C; Jain, Anil K; Agarwal, Chapla; Agarwal, Rajesh

2014-03-01

Currently, there are limited therapeutic options against bone metastatic prostate cancer (PCA), which is primarily responsible for high mortality and morbidity in PCA patients. Enhanced osteoclastogenesis is an essential feature associated with metastatic PCA in the bone microenvironment. Silibinin, an effective chemopreventive agent, is in phase II clinical trials in PCA patients but its efficacy against PCA cells-induced osteoclastogenesis is largely unknown. Accordingly, here we examined silibinin effect on PCA cells-induced osteoclastogenesis employing human PCA (PC3MM2, PC3, and C4-2B) and murine macrophage RAW264.7 cells. We also assessed silibinin effect on receptor activator of nuclear factor κB ligand (RANKL)-induced signaling associated with osteoclast differentiation in RAW264.7 cells. Further, we analyzed silibinin effect on osteomimicry biomarkers in PCA cells. Results revealed that silibinin (30-90 μM) inhibits PCA cells-induced osteoclast activity and differentiation in RAW264.7 cells via modulating expression of several cytokines (IGF-1, TGF-β, TNF-α, I-TAC, M-CSF, G-CSF, GM-CSF, etc.) that are important in osteoclastogenesis. Additionally, in RAW264.7 cells, silibinin decreased the RANKL-induced expression and nuclear localization of NFATc1, which is considered the master regulator of osteoclastogenesis. Furthermore, silibinin decreased the RANKL-induced DNA binding activity of NFATc1 and its regulators NF-κB and AP1, and the protein expression of osteoclast specific markers (TRAP, OSCAR, and cathepsin K). Importantly, silibinin also decreased the expression of osteomimicry biomarkers (RANKL, Runx2, osteocalcin, and PTHrP) in cell culture (PC3 and C4-2B cells) and/or in PC3 tumors. Together, our findings showing that silibinin inhibits PCA cells-induced osteoclastogenesis, suggest that silibinin could be useful clinically against bone metastatic PCA. © 2013 Wiley Periodicals, Inc.

A Systematic Review and Meta-analysis of the Diagnostic Accuracy of Prostate Health Index and 4-Kallikrein Panel Score in Predicting Overall and High-grade Prostate Cancer.

PubMed

Russo, Giorgio Ivan; Regis, Federica; Castelli, Tommaso; Favilla, Vincenzo; Privitera, Salvatore; Giardina, Raimondo; Cimino, Sebastiano; Morgia, Giuseppe

2017-08-01

Markers for prostate cancer (PCa) have progressed over recent years. In particular, the prostate health index (PHI) and the 4-kallikrein (4K) panel have been demonstrated to improve the diagnosis of PCa. We aimed to review the diagnostic accuracy of PHI and the 4K panel for PCa detection. We performed a systematic literature search of PubMed, EMBASE, Cochrane, and Academic One File databases until July 2016. We included diagnostic accuracy studies that used PHI or 4K panel for the diagnosis of PCa or high-grade PCa. The methodological quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool. Twenty-eight studies including 16,762 patients have been included for the analysis. The pooled data showed a sensitivity of 0.89 and 0.74 for PHI and 4K panel, respectively, for PCa detection and a pooled specificity of 0.34 and 0.60 for PHI and 4K panel, respectively. The derived area under the curve (AUC) from the hierarchical summary receiver operating characteristic (HSROC) showed an accuracy of 0.76 and 0.72 for PHI and 4K panel respectively. For high-grade PCa detection, the pooled sensitivity was 0.93 and 0.87 for PHI and 4K panel, respectively, whereas the pooled specificity was 0.34 and 0.61 for PHI and 4K panel, respectively. The derived AUC from the HSROC showed an accuracy of 0.82 and 0.81 for PHI and 4K panel, respectively. Both PHI and the 4K panel provided good diagnostic accuracy in detecting overall and high-grade PCa. Copyright © 2016 Elsevier Inc. All rights reserved.

Urinary MicroRNAs of Prostate Cancer: Virus-Encoded hsv1-miRH18 and hsv2-miR-H9-5p Could Be Valuable Diagnostic Markers.

PubMed

Yun, Seok Joong; Jeong, Pildu; Kang, Ho Won; Kim, Ye-Hwan; Kim, Eun-Ah; Yan, Chunri; Choi, Young-Ki; Kim, Dongho; Kim, Jung Min; Kim, Seon-Kyu; Kim, Seon-Young; Kim, Sang Tae; Kim, Won Tae; Lee, Ok-Jun; Koh, Gou-Young; Moon, Sung-Kwon; Kim, Isaac Yi; Kim, Jayoung; Choi, Yung-Hyun; Kim, Wun-Jae

2015-06-01

MicroRNAs (miRNAs) in biological fluids are potential biomarkers for the diagnosis and assessment of urological diseases such as benign prostatic hyperplasia (BPH) and prostate cancer (PCa). The aim of the study was to identify and validate urinary cell-free miRNAs that can segregate patients with PCa from those with BPH. In total, 1,052 urine, 150 serum, and 150 prostate tissue samples from patients with PCa or BPH were used in the study. A urine-based miRNA microarray analysis suggested the presence of differentially expressed urinary miRNAs in patients with PCa, and these were further validated in three independent PCa cohorts, using a quantitative reverse transcriptionpolymerase chain reaction analysis. The expression levels of hsa-miR-615-3p, hsv1-miR-H18, hsv2-miR-H9-5p, and hsa-miR-4316 were significantly higher in urine samples of patients with PCa than in those of BPH controls. In particular, herpes simplex virus (hsv)-derived hsv1-miR-H18 and hsv2-miR-H9-5p showed better diagnostic performance than did the serum prostate-specific antigen (PSA) test for patients in the PSA gray zone. Furthermore, a combination of urinary hsv2-miR-H9-5p with serum PSA showed high sensitivity and specificity, providing a potential clinical benefit by reducing unnecessary biopsies. Our findings showed that hsv-encoded hsv1-miR-H18 and hsv2-miR-H9-5p are significantly associated with PCa and can facilitate early diagnosis of PCa for patients within the serum PSA gray zone.

Urinary MicroRNAs of Prostate Cancer: Virus-Encoded hsv1-miRH18 and hsv2-miR-H9-5p Could Be Valuable Diagnostic Markers

PubMed Central

Yun, Seok Joong; Jeong, Pildu; Kang, Ho Won; Kim, Ye-Hwan; Kim, Eun-Ah; Yan, Chunri; Choi, Young-Ki; Kim, Dongho; Kim, Jung Min; Kim, Seon-Kyu; Kim, Seon-Young; Kim, Sang Tae; Kim, Won Tae; Lee, Ok-Jun; Koh, Gou-Young; Moon, Sung-Kwon; Kim, Isaac Yi; Kim, Jayoung; Choi, Yung-Hyun; Kim, Wun-Jae

2015-01-01

Purpose: MicroRNAs (miRNAs) in biological fluids are potential biomarkers for the diagnosis and assessment of urological diseases such as benign prostatic hyperplasia (BPH) and prostate cancer (PCa). The aim of the study was to identify and validate urinary cell-free miRNAs that can segregate patients with PCa from those with BPH. Methods: In total, 1,052 urine, 150 serum, and 150 prostate tissue samples from patients with PCa or BPH were used in the study. A urine-based miRNA microarray analysis suggested the presence of differentially expressed urinary miRNAs in patients with PCa, and these were further validated in three independent PCa cohorts, using a quantitative reverse transcriptionpolymerase chain reaction analysis. Results: The expression levels of hsa-miR-615-3p, hsv1-miR-H18, hsv2-miR-H9-5p, and hsa-miR-4316 were significantly higher in urine samples of patients with PCa than in those of BPH controls. In particular, herpes simplex virus (hsv)-derived hsv1-miR-H18 and hsv2-miR-H9-5p showed better diagnostic performance than did the serum prostate-specific antigen (PSA) test for patients in the PSA gray zone. Furthermore, a combination of urinary hsv2-miR-H9-5p with serum PSA showed high sensitivity and specificity, providing a potential clinical benefit by reducing unnecessary biopsies. Conclusions: Our findings showed that hsv-encoded hsv1-miR-H18 and hsv2-miR-H9-5p are significantly associated with PCa and can facilitate early diagnosis of PCa for patients within the serum PSA gray zone. PMID:26126436

Identification and suppression of the p-coumaroyl CoA:hydroxycinnamyl alcohol transferase in Zea mays L.

PubMed Central

Marita, Jane M; Hatfield, Ronald D; Rancour, David M; Frost, Kenneth E

2014-01-01

Grasses, such as Zea mays L. (maize), contain relatively high levels of p-coumarates (pCA) within their cell walls. Incorporation of pCA into cell walls is believed to be due to a hydroxycinnamyl transferase that couples pCA to monolignols. To understand the role of pCA in maize development, the p-coumaroyl CoA:hydroxycinnamyl alcohol transferase (pCAT) was isolated and purified from maize stems. Purified pCAT was subjected to partial trypsin digestion, and peptides were sequenced by tandem mass spectrometry. TBLASTN analysis of the acquired peptide sequences identified a single full-length maize cDNA clone encoding all the peptide sequences obtained from the purified enzyme. The cDNA clone was obtained and used to generate an RNAi construct for suppressing pCAT expression in maize. Here we describe the effects of suppression of pCAT in maize. Primary screening of transgenic maize seedling leaves using a new rapid analytical platform was used to identify plants with decreased amounts of pCA. Using this screening method, mature leaves from fully developed plants were analyzed, confirming reduced pCA levels throughout plant development. Complete analysis of isolated cell walls from mature transgenic stems and leaves revealed that lignin levels did not change, but pCA levels decreased and the lignin composition was altered. Transgenic plants with the lowest levels of pCA had decreased levels of syringyl units in the lignin. Thus, altering the levels of pCAT expression in maize leads to altered lignin composition, but does not appear to alter the total amount of lignin present in the cell walls. PMID:24654730

Novel potential serological prostate cancer biomarkers using CT100+ cancer antigen microarray platform in a multi-cultural South African cohort

PubMed Central

Adeola, Henry A.; Smith, Muneerah; Kaestner, Lisa; Blackburn, Jonathan M.; Zerbini, Luiz F.

2016-01-01

There is a growing need for high throughput diagnostic tools for early diagnosis and treatment monitoring of prostate cancer (PCa) in Africa. The role of cancer-testis antigens (CTAs) in PCa in men of African descent is poorly researched. Hence, we aimed to elucidate the role of 123 Tumour Associated Antigens (TAAs) using antigen microarray platform in blood samples (N = 67) from a South African PCa, Benign prostatic hyperplasia (BPH) and disease control (DC) cohort. Linear (fold-over-cutoff) and differential expression quantitation of autoantibody signal intensities were performed. Molecular signatures of candidate PCa antigen biomarkers were identified and analyzed for ethnic group variation. Potential cancer diagnostic and immunotherapeutic inferences were drawn. We identified a total of 41 potential diagnostic/therapeutic antigen biomarkers for PCa. By linear quantitation, four antigens, GAGE1, ROPN1, SPANXA1 and PRKCZ were found to have higher autoantibody titres in PCa serum as compared with BPH where MAGEB1 and PRKCZ were highly expressed. Also, p53 S15A and p53 S46A were found highly expressed in the disease control group. Statistical analysis by differential expression revealed twenty-four antigens as upregulated in PCa samples, while 11 were downregulated in comparison to BPH and DC (FDR = 0.01). FGFR2, COL6A1and CALM1 were verifiable biomarkers of PCa analysis using urinary shotgun proteomics. Functional pathway annotation of identified biomarkers revealed similar enrichment both at genomic and proteomic level and ethnic variations were observed. Cancer antigen arrays are emerging useful in potential diagnostic and immunotherapeutic antigen biomarker discovery. PMID:26885621

Identification and suppression of the p-coumaroyl CoA:hydroxycinnamyl alcohol transferase in Zea mays L.

PubMed

Marita, Jane M; Hatfield, Ronald D; Rancour, David M; Frost, Kenneth E

2014-06-01

Grasses, such as Zea mays L. (maize), contain relatively high levels of p-coumarates (pCA) within their cell walls. Incorporation of pCA into cell walls is believed to be due to a hydroxycinnamyl transferase that couples pCA to monolignols. To understand the role of pCA in maize development, the p-coumaroyl CoA:hydroxycinnamyl alcohol transferase (pCAT) was isolated and purified from maize stems. Purified pCAT was subjected to partial trypsin digestion, and peptides were sequenced by tandem mass spectrometry. TBLASTN analysis of the acquired peptide sequences identified a single full-length maize cDNA clone encoding all the peptide sequences obtained from the purified enzyme. The cDNA clone was obtained and used to generate an RNAi construct for suppressing pCAT expression in maize. Here we describe the effects of suppression of pCAT in maize. Primary screening of transgenic maize seedling leaves using a new rapid analytical platform was used to identify plants with decreased amounts of pCA. Using this screening method, mature leaves from fully developed plants were analyzed, confirming reduced pCA levels throughout plant development. Complete analysis of isolated cell walls from mature transgenic stems and leaves revealed that lignin levels did not change, but pCA levels decreased and the lignin composition was altered. Transgenic plants with the lowest levels of pCA had decreased levels of syringyl units in the lignin. Thus, altering the levels of pCAT expression in maize leads to altered lignin composition, but does not appear to alter the total amount of lignin present in the cell walls. © 2014 The Authors The Plant Journal © 2014 John Wiley & Sons Ltd.

Predictive spectroscopy and chemical imaging based on novel optical systems

NASA Astrophysics Data System (ADS)

Nelson, Matthew Paul

1998-10-01

This thesis describes two futuristic optical systems designed to surpass contemporary spectroscopic methods for predictive spectroscopy and chemical imaging. These systems are advantageous to current techniques in a number of ways including lower cost, enhanced portability, shorter analysis time, and improved S/N. First, a novel optical approach to predicting chemical and physical properties based on principal component analysis (PCA) is proposed and evaluated. A regression vector produced by PCA is designed into the structure of a set of paired optical filters. Light passing through the paired filters produces an analog detector signal directly proportional to the chemical/physical property for which the regression vector was designed. Second, a novel optical system is described which takes a single-shot approach to chemical imaging with high spectroscopic resolution using a dimension-reduction fiber-optic array. Images are focused onto a two- dimensional matrix of optical fibers which are drawn into a linear distal array with specific ordering. The distal end is imaged with a spectrograph equipped with an ICCD camera for spectral analysis. Software is used to extract the spatial/spectral information contained in the ICCD images and deconvolute them into wave length-specific reconstructed images or position-specific spectra which span a multi-wavelength space. This thesis includes a description of the fabrication of two dimension-reduction arrays as well as an evaluation of the system for spatial and spectral resolution, throughput, image brightness, resolving power, depth of focus, and channel cross-talk. PCA is performed on the images by treating rows of the ICCD images as spectra and plotting the scores of each PC as a function of reconstruction position. In addition, iterative target transformation factor analysis (ITTFA) is performed on the spectroscopic images to generate ``true'' chemical maps of samples. Univariate zero-order images, univariate first-order spectroscopic images, bivariate first-order spectroscopic images, and multivariate first-order spectroscopic images of the temporal development of laser-induced plumes are presented and interpreted. Reconstructed chemical images generated using bivariate and trivariate wavelength techniques, bimodal and trimodal PCA methods, and bimodal and trimodal ITTFA approaches are also included.

Automated pre-processing and multivariate vibrational spectra analysis software for rapid results in clinical settings

NASA Astrophysics Data System (ADS)

Bhattacharjee, T.; Kumar, P.; Fillipe, L.

2018-02-01

Vibrational spectroscopy, especially FTIR and Raman, has shown enormous potential in disease diagnosis, especially in cancers. Their potential for detecting varied pathological conditions are regularly reported. However, to prove their applicability in clinics, large multi-center multi-national studies need to be undertaken; and these will result in enormous amount of data. A parallel effort to develop analytical methods, including user-friendly software that can quickly pre-process data and subject them to required multivariate analysis is warranted in order to obtain results in real time. This study reports a MATLAB based script that can automatically import data, preprocess spectra— interpolation, derivatives, normalization, and then carry out Principal Component Analysis (PCA) followed by Linear Discriminant Analysis (LDA) of the first 10 PCs; all with a single click. The software has been verified on data obtained from cell lines, animal models, and in vivo patient datasets, and gives results comparable to Minitab 16 software. The software can be used to import variety of file extensions, asc, .txt., .xls, and many others. Options to ignore noisy data, plot all possible graphs with PCA factors 1 to 5, and save loading factors, confusion matrices and other parameters are also present. The software can provide results for a dataset of 300 spectra within 0.01 s. We believe that the software will be vital not only in clinical trials using vibrational spectroscopic data, but also to obtain rapid results when these tools get translated into clinics.

Assessment of compost maturity by using an electronic nose.

PubMed

López, Rafael; Giráldez, Inmaculada; Palma, Alberto; Jesús Díaz, M

2016-02-01

The composting process produces and emits hundreds of different gases. Volatile organic compounds (VOCs) can provide information about progress of composting process. This paper is focused on the qualitative and quantitative relationships between compost age, as sign of compost maturity, electronic-nose (e-nose) patterns and composition of compost and composting gas at an industrial scale plant. Gas and compost samples were taken at different depths from composting windrows of different ages. Temperature, classical chemical parameters, O2, CO, combustible gases, VOCs and e-nose profiles were determined and related using principal component analysis (PCA). Factor analysis carried out to a data set including compost physical-chemical properties, pile pore gas composition and composting time led to few factors, each one grouping together standard composting parameters in an easy to understand way. PCA obtained from e-nose profiles allowed the classifying of piles, their aerobic-anaerobic condition, and a rough estimation of the composting time. That would allow for immediate and in-situ assessment of compost quality and maturity by using an on-line e-nose. The e-nose patterns required only 3-4 sensor signals to account for a great percentage (97-98%) of data variance. The achieved patterns both from compost (chemical analysis) and gas (e-nose analysis) samples are robust despite the high variability in feedstock characteristics (3 different materials), composting conditions and long composting time. GC-MS chromatograms supported the patterns. Copyright © 2015 Elsevier Ltd. All rights reserved.

Income and health-related quality of life among prostate cancer patients over a one-year period after radical prostatectomy: a linear mixed model analysis.

PubMed

Klein, Jens; Lüdecke, Daniel; Hofreuter-Gätgens, Kerstin; Fisch, Margit; Graefen, Markus; von dem Knesebeck, Olaf

2017-09-01

To examine income-related disparities in health-related quality of life (HRQOL) over a one-year period after surgery (radical prostatectomy) and its contributory factors in a longitudinal perspective. Evidence of associations between income and HRQOL among patients with prostate cancer (PCa) is sparse and their explanations still remain unclear. 246 males of two German hospitals filled out a questionnaire at the time of acute treatment, 6 and 12 months later. Age, partnership status, baseline disease and treatment factors, physical and psychological comorbidities, as well as treatment factors and adverse effects at follow-up were additionally included in the analyses to explain potential disparities. HRQOL was assessed with the EORTC (European Organisation for Research and Treatment of Cancer) QLQ-C30 core questionnaire and the prostate-specific QLQ-PR25. A linear mixed model for repeated measures was calculated. The fixed effects showed highly significant income-related inequalities regarding the majority of HRQOL scales. Less affluent PCa patients reported lower HRQOL in terms of global quality of life, all functional scales and urinary symptoms. After introducing relevant covariates, some associations became insignificant (physical, cognitive and sexual function), while others only showed reduced estimates (global quality of life, urinary symptoms, role, emotional and social function). In particular, mental disorders/psychological comorbidity played a relevant role in the explanation of income-related disparities. One year after surgery, income-related disparities in various dimensions of HRQOL persist. With respect to economically disadvantaged PCa patients, the findings emphasize the importance of continuous psychosocial screening and tailored interventions, of patients' empowerment and improved access to supportive care.

Frequency of Propionibacterium acnes Infection in Prostate Glands with Negative Biopsy Results Is an Independent Risk Factor for Prostate Cancer in Patients with Increased Serum PSA Titers

PubMed Central

Ito, Takashi; Uchida, Keisuke; Sekine, Masaki; Nakajima, Yutaka; Furukawa, Asuka; Suzuki, Yoshimi; Kumagai, Jiro; Akashi, Takumi

2017-01-01

Background Propionibacterium acnes has recently been implicated as a cause of chronic prostatitis and this commensal bacterium may be linked to prostate carcinogenesis. The occurrence of intracellular P. acnes infection in prostate glands and the higher frequency of P. acnes-positive glands in radical prostatectomy specimens from patients with prostate cancer (PCa) than in those from patients without PCa led us to examine whether the P. acnes-positive gland frequency can be used to assess the risk for PCa in patients whose first prostate biopsy, performed due to an increased prostate-specific antigen (PSA) titer, was negative. Methods We retrospectively collected the first and last prostate biopsy samples from 44 patients that were diagnosed PCa within 4 years after the first negative biopsy and from 36 control patients with no PCa found in repeated biopsy for at least 3 years after the first biopsy. We evaluated P. acnes-positive gland frequency and P. acnes-positive macrophage number using enzyme-immunohistochemistry with a P. acnes-specific monoclonal antibody (PAL antibody). Results The frequency of P. acnes-positive glands was higher in PCa samples than in control samples in both first biopsy samples and in combined first and last biopsy samples (P < 0.001). A frequency greater than the threshold (18.5 and 17.7, respectively) obtained by each receiver operating characteristic curve was an independent risk factor for PCa (P = 0.003 and 0.001, respectively) with odds ratios (14.8 and 13.9, respectively) higher than those of serum PSA titers of patients just before each biopsy (4.6 and 2.3, respectively). The number of P. acnes-positive macrophages did not differ significantly between PCa and control samples. Conclusions These results suggested that the frequency of P. acnes-positive glands in the first negative prostate biopsy performed due to increased PSA titers can be supportive information for urologists in planning repeated biopsy or follow-up strategies. PMID:28081259

Vision-based method for detecting driver drowsiness and distraction in driver monitoring system

NASA Astrophysics Data System (ADS)

Jo, Jaeik; Lee, Sung Joo; Jung, Ho Gi; Park, Kang Ryoung; Kim, Jaihie

2011-12-01

Most driver-monitoring systems have attempted to detect either driver drowsiness or distraction, although both factors should be considered for accident prevention. Therefore, we propose a new driver-monitoring method considering both factors. We make the following contributions. First, if the driver is looking ahead, drowsiness detection is performed; otherwise, distraction detection is performed. Thus, the computational cost and eye-detection error can be reduced. Second, we propose a new eye-detection algorithm that combines adaptive boosting, adaptive template matching, and blob detection with eye validation, thereby reducing the eye-detection error and processing time significantly, which is hardly achievable using a single method. Third, to enhance eye-detection accuracy, eye validation is applied after initial eye detection, using a support vector machine based on appearance features obtained by principal component analysis (PCA) and linear discriminant analysis (LDA). Fourth, we propose a novel eye state-detection algorithm that combines appearance features obtained using PCA and LDA, with statistical features such as the sparseness and kurtosis of the histogram from the horizontal edge image of the eye. Experimental results showed that the detection accuracies of the eye region and eye states were 99 and 97%, respectively. Both driver drowsiness and distraction were detected with a success rate of 98%.

Development and Validation of a Questionnaire on Breastfeeding Intentions, Attitudes and Knowledge of a Sample of Croatian Secondary-School Students.

PubMed

Čatipović, Marija; Marković, Martina; Grgurić, Josip

2018-04-27

Validating a questionnaire/instrument before proceeding to the field for data collection is important. An 18-item breastfeeding intention, 39-item attitude and 44-item knowledge questionnaire was validated in a Croatian sample of secondary-school students ( N = 277). For the intentions, principal component analysis (PCA) yielded a four-factor solution with 8 items explaining 68.3% of the total variance. Cronbach’s alpha (0.71) indicated satisfactory internal consistency. For the attitudes, PCA showed a seven-factor structure with 33 items explaining 58.41% of total variance. Cronbach’s alpha (0.87) indicated good internal consistency. There were 13 knowledge questions that were retained after item analysis, showing good internal consistency (KR20 = 0.83). In terms of criterion validity, the questionnaire differentiated between students who received breastfeeding education compared to students who were not educated in breastfeeding. Correlations between intentions and attitudes (r = 0.49), intentions and knowledge (r = 0.29), and attitudes and knowledge (r = 0.38) confirmed concurrent validity. The final instrument is reliable and valid for data collection on breastfeeding. Therefore, the instrument is recommended for evaluation of breastfeeding education programs aimed at upper-grade elementary and secondary school students.

Development and Validation of a Questionnaire on Breastfeeding Intentions, Attitudes and Knowledge of a Sample of Croatian Secondary-School Students

PubMed Central

Marković, Martina; Grgurić, Josip

2018-01-01

Background: Validating a questionnaire/instrument before proceeding to the field for data collection is important. Methods: An 18-item breastfeeding intention, 39-item attitude and 44-item knowledge questionnaire was validated in a Croatian sample of secondary-school students (N = 277). Results: For the intentions, principal component analysis (PCA) yielded a four-factor solution with 8 items explaining 68.3% of the total variance. Cronbach’s alpha (0.71) indicated satisfactory internal consistency. For the attitudes, PCA showed a seven-factor structure with 33 items explaining 58.41% of total variance. Cronbach’s alpha (0.87) indicated good internal consistency. There were 13 knowledge questions that were retained after item analysis, showing good internal consistency (KR20 = 0.83). In terms of criterion validity, the questionnaire differentiated between students who received breastfeeding education compared to students who were not educated in breastfeeding. Correlations between intentions and attitudes (r = 0.49), intentions and knowledge (r = 0.29), and attitudes and knowledge (r = 0.38) confirmed concurrent validity. Conclusions: The final instrument is reliable and valid for data collection on breastfeeding. Therefore, the instrument is recommended for evaluation of breastfeeding education programs aimed at upper-grade elementary and secondary school students. PMID:29702616

Facilitating text reading in posterior cortical atrophy.

PubMed

Yong, Keir X X; Rajdev, Kishan; Shakespeare, Timothy J; Leff, Alexander P; Crutch, Sebastian J

2015-07-28

We report (1) the quantitative investigation of text reading in posterior cortical atrophy (PCA), and (2) the effects of 2 novel software-based reading aids that result in dramatic improvements in the reading ability of patients with PCA. Reading performance, eye movements, and fixations were assessed in patients with PCA and typical Alzheimer disease and in healthy controls (experiment 1). Two reading aids (single- and double-word) were evaluated based on the notion that reducing the spatial and oculomotor demands of text reading might support reading in PCA (experiment 2). Mean reading accuracy in patients with PCA was significantly worse (57%) compared with both patients with typical Alzheimer disease (98%) and healthy controls (99%); spatial aspects of passages were the primary determinants of text reading ability in PCA. Both aids led to considerable gains in reading accuracy (PCA mean reading accuracy: single-word reading aid = 96%; individual patient improvement range: 6%-270%) and self-rated measures of reading. Data suggest a greater efficiency of fixations and eye movements under the single-word reading aid in patients with PCA. These findings demonstrate how neurologic characterization of a neurodegenerative syndrome (PCA) and detailed cognitive analysis of an important everyday skill (reading) can combine to yield aids capable of supporting important everyday functional abilities. This study provides Class III evidence that for patients with PCA, 2 software-based reading aids (single-word and double-word) improve reading accuracy. © 2015 American Academy of Neurology.

Facilitating text reading in posterior cortical atrophy

PubMed Central

Rajdev, Kishan; Shakespeare, Timothy J.; Leff, Alexander P.; Crutch, Sebastian J.

2015-01-01

Objective: We report (1) the quantitative investigation of text reading in posterior cortical atrophy (PCA), and (2) the effects of 2 novel software-based reading aids that result in dramatic improvements in the reading ability of patients with PCA. Methods: Reading performance, eye movements, and fixations were assessed in patients with PCA and typical Alzheimer disease and in healthy controls (experiment 1). Two reading aids (single- and double-word) were evaluated based on the notion that reducing the spatial and oculomotor demands of text reading might support reading in PCA (experiment 2). Results: Mean reading accuracy in patients with PCA was significantly worse (57%) compared with both patients with typical Alzheimer disease (98%) and healthy controls (99%); spatial aspects of passages were the primary determinants of text reading ability in PCA. Both aids led to considerable gains in reading accuracy (PCA mean reading accuracy: single-word reading aid = 96%; individual patient improvement range: 6%–270%) and self-rated measures of reading. Data suggest a greater efficiency of fixations and eye movements under the single-word reading aid in patients with PCA. Conclusions: These findings demonstrate how neurologic characterization of a neurodegenerative syndrome (PCA) and detailed cognitive analysis of an important everyday skill (reading) can combine to yield aids capable of supporting important everyday functional abilities. Classification of evidence: This study provides Class III evidence that for patients with PCA, 2 software-based reading aids (single-word and double-word) improve reading accuracy. PMID:26138948

Age-dependent modulation of serum IgE and mast cell sensitization by Nippostrongylus brasiliensis infestation in rats.

PubMed

Turner, K J; Fisher, E H; Mayrhofer, G

1981-08-01

The capacity of N. brasiliensis (Nb) infestation to modify synthesis of ovalbumin (OV) specific IgE antibody was monitored in weanling, juvenile and adult female WAG rats by both passive cutaneous anaphylaxis (PCA) activity and by a rat radio-allergosorbent test (RAST). Infestation with Nb larvae 10 days after immunization with OV produced marginal potentiation of anti-OV Ig antibody production by both RAST and PCA in weanlings, marginal suppression by both parameters in juveniles and was without effect in adults. However, immunization with OV after infestation with Nb partially suppressed anti-OV IgE antibody production in weanlings (RAST) and totally abolished the PCA activity. Although this regime did not impair anti-OV IgE antibody synthesis (RAST) in juveniles, the sera were PCA-negative. In contrast, normal responses were found in adult rats. Negative PCA titres in sera containing high levels of specific antibody occurred when serum total IgE levels were elevated, and are explained on the basis of competition for binding sites on mast cells. The ratio of OV-specific IgE to 'total' IgE is a critical factor in detecting PCA activity.

Analysis of environmental variation in a Great Plains reservoir using principal components analysis and geographic information systems

USGS Publications Warehouse

Long, J.M.; Fisher, W.L.

2006-01-01

We present a method for spatial interpretation of environmental variation in a reservoir that integrates principal components analysis (PCA) of environmental data with geographic information systems (GIS). To illustrate our method, we used data from a Great Plains reservoir (Skiatook Lake, Oklahoma) with longitudinal variation in physicochemical conditions. We measured 18 physicochemical features, mapped them using GIS, and then calculated and interpreted four principal components. Principal component 1 (PC1) was readily interpreted as longitudinal variation in water chemistry, but the other principal components (PC2-4) were difficult to interpret. Site scores for PC1-4 were calculated in GIS by summing weighted overlays of the 18 measured environmental variables, with the factor loadings from the PCA as the weights. PC1-4 were then ordered into a landscape hierarchy, an emergent property of this technique, which enabled their interpretation. PC1 was interpreted as a reservoir scale change in water chemistry, PC2 was a microhabitat variable of rip-rap substrate, PC3 identified coves/embayments and PC4 consisted of shoreline microhabitats related to slope. The use of GIS improved our ability to interpret the more obscure principal components (PC2-4), which made the spatial variability of the reservoir environment more apparent. This method is applicable to a variety of aquatic systems, can be accomplished using commercially available software programs, and allows for improved interpretation of the geographic environmental variability of a system compared to using typical PCA plots. ?? Copyright by the North American Lake Management Society 2006.

Korean, Japanese, and Chinese populations featured similar genes encoding drug-metabolizing enzymes and transporters: a DMET Plus microarray assessment.

PubMed

Yi, SoJeong; An, Hyungmi; Lee, Howard; Lee, Sangin; Ieiri, Ichiro; Lee, Youngjo; Cho, Joo-Youn; Hirota, Takeshi; Fukae, Masato; Yoshida, Kenji; Nagatsuka, Shinichiro; Kimura, Miyuki; Irie, Shin; Sugiyama, Yuichi; Shin, Dong Wan; Lim, Kyoung Soo; Chung, Jae-Yong; Yu, Kyung-Sang; Jang, In-Jin

2014-10-01

Interethnic differences in genetic polymorphism in genes encoding drug-metabolizing enzymes and transporters are one of the major factors that cause ethnic differences in drug response. This study aimed to investigate genetic polymorphisms in genes involved in drug metabolism, transport, and excretion among Korean, Japanese, and Chinese populations, the three major East Asian ethnic groups. The frequencies of 1936 variants representing 225 genes encoding drug-metabolizing enzymes and transporters were determined from 786 healthy participants (448 Korean, 208 Japanese, and 130 Chinese) using the Affymetrix Drug-Metabolizing Enzymes and Transporters Plus microarray. To compare allele or genotype frequencies in the high-dimensional data among the three East Asian ethnic groups, multiple testing, principal component analysis (PCA), and regularized multinomial logit model through least absolute shrinkage and selection operator were used. On microarray analysis, 1071 of 1936 variants (>50% of markers) were found to be monomorphic. In a large number of genetic variants, the fixation index and Pearson's correlation coefficient of minor allele frequencies were less than 0.034 and greater than 0.95, respectively, among the three ethnic groups. PCA identified 47 genetic variants with multiple testing, but was unable to discriminate ethnic groups by the first three components. Multinomial least absolute shrinkage and selection operator analysis identified 269 genetic variants that showed different frequencies among the three ethnic groups. However, none of those variants distinguished between the three ethnic groups during subsequent PCA. Korean, Japanese, and Chinese populations are not pharmacogenetically distant from one another, at least with regard to drug disposition, metabolism, and elimination.

Conformational flexibility of the ErbB2 ectodomain and trastuzumab antibody complex as revealed by molecular dynamics and principal component analysis.

PubMed

Franco-Gonzalez, Juan Felipe; Cruz, Victor L; Ramos, Javier; Martínez-Salazar, Javier

2013-03-01

Human epidermal growth factor receptor 2 (ErbB2) is a transmembrane oncoprotein that is over expressed in breast cancer. A successful therapeutic treatment is a monoclonal antibody called trastuzumab which interacts with the ErbB2 extracellular domain (ErbB2-ECD). A better understanding of the detailed structure of the receptor-antibody interaction is indeed of prime interest for the design of more effective anticancer therapies. In order to discuss the flexibility of the complex ErbB2-ECD/trastuzumab, we present, in this study, a multi-nanosecond molecular dynamics simulation (MD) together with an analysis of fluctuations, through a principal component analysis (PCA) of this system. Previous to this step and in order to validate the simulations, we have performed a detailed analysis of the variable antibody domain interactions with the extracellular domain IV of ErbB2. This structure has been statically elucidated by x-ray studies. Indeed, the simulation results are in excellent agreement with the available experimental information during the full trajectory. The PCA shows eigenvector fluctuations resulting in a hinge motion in which domain II and C(H) domains approach each other. This move is likely stabilized by the formation of H-bonds and salt bridge interactions between residues of the dimerization arm in the domain II and trastuzumab residues located in the C(H) domain. Finally, we discuss the flexibility of the MD/PCA model in relation with the static x-ray structure. A movement of the antibody toward the dimerization domain of the ErbB2 receptor is reported for the first time. This finding could have important consequences on the biological action of the monoclonal antibody.

Principal components analysis in clinical studies.

PubMed

Zhang, Zhongheng; Castelló, Adela

2017-09-01

In multivariate analysis, independent variables are usually correlated to each other which can introduce multicollinearity in the regression models. One approach to solve this problem is to apply principal components analysis (PCA) over these variables. This method uses orthogonal transformation to represent sets of potentially correlated variables with principal components (PC) that are linearly uncorrelated. PCs are ordered so that the first PC has the largest possible variance and only some components are selected to represent the correlated variables. As a result, the dimension of the variable space is reduced. This tutorial illustrates how to perform PCA in R environment, the example is a simulated dataset in which two PCs are responsible for the majority of the variance in the data. Furthermore, the visualization of PCA is highlighted.

Discriminative non-negative matrix factorization (DNMF) and its application to the fault diagnosis of diesel engine

NASA Astrophysics Data System (ADS)

Yang, Yong-sheng; Ming, An-bo; Zhang, You-yun; Zhu, Yong-sheng

2017-10-01

Diesel engines, widely used in engineering, are very important for the running of equipments and their fault diagnosis have attracted much attention. In the past several decades, the image based fault diagnosis methods have provided efficient ways for the diesel engine fault diagnosis. By introducing the class information into the traditional non-negative matrix factorization (NMF), an improved NMF algorithm named as discriminative NMF (DNMF) was developed and a novel imaged based fault diagnosis method was proposed by the combination of the DNMF and the KNN classifier. Experiments performed on the fault diagnosis of diesel engine were used to validate the efficacy of the proposed method. It is shown that the fault conditions of diesel engine can be efficiently classified by the proposed method using the coefficient matrix obtained by DNMF. Compared with the original NMF (ONMF) and principle component analysis (PCA), the DNMF can represent the class information more efficiently because the class characters of basis matrices obtained by the DNMF are more visible than those in the basis matrices obtained by the ONMF and PCA.

Collaborative Review: Risk-Based Prostate Cancer Screening

PubMed Central

Zhu, Xiaoye; Albertsen, Peter C.; Andriole, Gerald L.; Roobol, Monique J.; Schröder, Fritz H.; Vickers, Andrew J.

2016-01-01

Context Widespread mass screening of prostate cancer (PCa) is not recommended because the balance between benefits and harms is still not well established. The achieved mortality reduction comes with considerable harm such as unnecessary biopsies, overdiagnoses, and overtreatment. Therefore, patient stratification with regard to PCa risk and aggressiveness is necessary to identify those men who are at risk and may actually benefit from early detection. Objective This review critically examines the current evidence regarding risk-based PCa screening. Evidence acquisition A search of the literature was performed using the Medline database. Further studies were selected based on manual searches of reference lists and review articles. Evidence synthesis Prostate-specific antigen (PSA) has been shown to be the single most significant predictive factor for identifying men at increased risk of developing PCa. Especially in men with no additional risk factors, PSA alone provides an appropriate marker up to 30 yr into the future. After assessment of an early PSA test, the screening frequency may be determined based on individualized risk. A limited list of additional factors such as age, comorbidity, prostate volume, family history, ethnicity, and previous biopsy status have been identified to modify risk and are important for consideration in routine practice. In men with a known PSA, risk calculators may hold the promise of identifying those who are at increased risk of having PCa and are therefore candidates for biopsy. Conclusions PSA testing may serve as the foundation for a more risk-based assessment. However, the decision to undergo early PSA testing should be a shared one between the patient and his physician based on information balancing its advantages and disadvantages. PMID:22134009

Selecting predictors for discriminant analysis of species performance: an example from an amphibious softwater plant.

PubMed

Vanderhaeghe, F; Smolders, A J P; Roelofs, J G M; Hoffmann, M

2012-03-01

Selecting an appropriate variable subset in linear multivariate methods is an important methodological issue for ecologists. Interest often exists in obtaining general predictive capacity or in finding causal inferences from predictor variables. Because of a lack of solid knowledge on a studied phenomenon, scientists explore predictor variables in order to find the most meaningful (i.e. discriminating) ones. As an example, we modelled the response of the amphibious softwater plant Eleocharis multicaulis using canonical discriminant function analysis. We asked how variables can be selected through comparison of several methods: univariate Pearson chi-square screening, principal components analysis (PCA) and step-wise analysis, as well as combinations of some methods. We expected PCA to perform best. The selected methods were evaluated through fit and stability of the resulting discriminant functions and through correlations between these functions and the predictor variables. The chi-square subset, at P < 0.05, followed by a step-wise sub-selection, gave the best results. In contrast to expectations, PCA performed poorly, as so did step-wise analysis. The different chi-square subset methods all yielded ecologically meaningful variables, while probable noise variables were also selected by PCA and step-wise analysis. We advise against the simple use of PCA or step-wise discriminant analysis to obtain an ecologically meaningful variable subset; the former because it does not take into account the response variable, the latter because noise variables are likely to be selected. We suggest that univariate screening techniques are a worthwhile alternative for variable selection in ecology. © 2011 German Botanical Society and The Royal Botanical Society of the Netherlands.

Multi-Centrality Graph Spectral Decompositions and Their Application to Cyber Intrusion Detection

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, Pin-Yu; Choudhury, Sutanay; Hero, Alfred

Many modern datasets can be represented as graphs and hence spectral decompositions such as graph principal component analysis (PCA) can be useful. Distinct from previous graph decomposition approaches based on subspace projection of a single topological feature, e.g., the centered graph adjacency matrix (graph Laplacian), we propose spectral decomposition approaches to graph PCA and graph dictionary learning that integrate multiple features, including graph walk statistics, centrality measures and graph distances to reference nodes. In this paper we propose a new PCA method for single graph analysis, called multi-centrality graph PCA (MC-GPCA), and a new dictionary learning method for ensembles ofmore » graphs, called multi-centrality graph dictionary learning (MC-GDL), both based on spectral decomposition of multi-centrality matrices. As an application to cyber intrusion detection, MC-GPCA can be an effective indicator of anomalous connectivity pattern and MC-GDL can provide discriminative basis for attack classification.« less

Revealing the ultrafast outflow in IRAS 13224-3809 through spectral variability

NASA Astrophysics Data System (ADS)

Parker, M. L.; Alston, W. N.; Buisson, D. J. K.; Fabian, A. C.; Jiang, J.; Kara, E.; Lohfink, A.; Pinto, C.; Reynolds, C. S.

2017-08-01

We present an analysis of the long-term X-ray variability of the extreme narrow-line Seyfert 1 galaxy IRAS 13224-3809 using principal component analysis (PCA) and fractional excess variability (Fvar) spectra to identify model-independent spectral components. We identify a series of variability peaks in both the first PCA component and Fvar spectrum which correspond to the strongest predicted absorption lines from the ultrafast outflow (UFO) discovered by Parker et al. (2017). We also find higher order PCA components, which correspond to variability of the soft excess and reflection features. The subtle differences between RMS and PCA results argue that the observed flux-dependence of the absorption is due to increased ionization of the gas, rather than changes in column density or covering fraction. This result demonstrates that we can detect outflows from variability alone and that variability studies of UFOs are an extremely promising avenue for future research.

Racism, Racial Resilience, and African American Youth Development: Person-Centered Analysis as a Tool to Promote Equity and Justice.

PubMed

Neblett, Enrique W; Sosoo, Effua E; Willis, Henry A; Bernard, Donte L; Bae, Jiwoon; Billingsley, Janelle T

Racism constitutes a significant risk to the healthy development of African American youth. Fortunately, however, not all youth who experience racism evidence negative developmental outcomes. In this chapter, we examine person-centered analysis (PCA)-a quantitative technique that investigates how variables combine across individuals-as a useful tool for elucidating racial and ethnic protective processes that mitigate the negative impact of racism. We review recent studies employing PCA in examinations of racial identity, racial socialization, and other race-related experiences, as well as how these constructs correlate with and impact African American youth development. We also consider challenges and limitations of PCA and conclude with a discussion of future research and how PCA might be used to promote equity and justice for African American and other racial and ethnic minority youth who experience racism. © 2016 Elsevier Inc. All rights reserved.

Finding imaging patterns of structural covariance via Non-Negative Matrix Factorization.

PubMed

Sotiras, Aristeidis; Resnick, Susan M; Davatzikos, Christos

2015-03-01

In this paper, we investigate the use of Non-Negative Matrix Factorization (NNMF) for the analysis of structural neuroimaging data. The goal is to identify the brain regions that co-vary across individuals in a consistent way, hence potentially being part of underlying brain networks or otherwise influenced by underlying common mechanisms such as genetics and pathologies. NNMF offers a directly data-driven way of extracting relatively localized co-varying structural regions, thereby transcending limitations of Principal Component Analysis (PCA), Independent Component Analysis (ICA) and other related methods that tend to produce dispersed components of positive and negative loadings. In particular, leveraging upon the well known ability of NNMF to produce parts-based representations of image data, we derive decompositions that partition the brain into regions that vary in consistent ways across individuals. Importantly, these decompositions achieve dimensionality reduction via highly interpretable ways and generalize well to new data as shown via split-sample experiments. We empirically validate NNMF in two data sets: i) a Diffusion Tensor (DT) mouse brain development study, and ii) a structural Magnetic Resonance (sMR) study of human brain aging. We demonstrate the ability of NNMF to produce sparse parts-based representations of the data at various resolutions. These representations seem to follow what we know about the underlying functional organization of the brain and also capture some pathological processes. Moreover, we show that these low dimensional representations favorably compare to descriptions obtained with more commonly used matrix factorization methods like PCA and ICA. Copyright © 2014 Elsevier Inc. All rights reserved.

Hemoglobin enhances tissue factor expression on human malignant cells.

PubMed

Siddiqui, F A; Amirkhosravi, A; Amaya, M; Meyer, T; Biggerstaff, J; Desai, H; Francis, J L

2001-04-01

Tissue Factor (TF) is a transmembrane glycoprotein that complexes with factor VII/activated factor VII to initiate blood coagulation. TF may be expressed on the surface of various cells including monocytes and endothelial cells. Over-expression of TF in human tumor cell lines promotes metastasis. We recently showed that hemoglobin (Hb) forms a specific complex with TF purified from human malignant melanoma cells and enhances its procoagulant activity (PCA). To further study this interaction, we examined the effect of Hb on the expression of TF on human malignant (TF+) cells and KG1 myeloid leukemia (TF-) cells. Human melanoma A375 and J82 bladder carcinoma cells, which express TF at moderate and relatively high levels, respectively, were incubated with varying concentrations (0-1.5 mg/ml) of Hb. After washing, cells were analyzed for Hb binding and TF expression using flow cytometry and confocal microscopy. Hb bound to the cells in a concentration-dependent manner, and increased both TF expression and PCA. The human A375 malignant melanoma cells incubated with Hb (1 mg/ml) expressed up to six times more TF antigen than cells without Hb. This increase in TF expression and PCA of intact cells incubated with Hb was significantly inhibited by cycloheximide at a concentration of 10 microg/ml (P < 0.01). An increase in total cellular TF antigen content was demonstrated by specific immunoassay. In contrast, Hb (5 mg/ml) did not induce TF expression and PCA on KG1 cells as determined by flow cytometry and TF (FXAA) activity. We conclude that Hb specifically binds to TF-bearing malignant cells and increases their PCA. This effect seems to be at least partly due to de novo synthesis of TF and increased surface expression. However, the exact mechanism by which Hb binds and upregulates TF expression remains to be determined.

Multiscale 3D Shape Analysis using Spherical Wavelets

PubMed Central

Nain, Delphine; Haker, Steven; Bobick, Aaron; Tannenbaum, Allen

2013-01-01

Shape priors attempt to represent biological variations within a population. When variations are global, Principal Component Analysis (PCA) can be used to learn major modes of variation, even from a limited training set. However, when significant local variations exist, PCA typically cannot represent such variations from a small training set. To address this issue, we present a novel algorithm that learns shape variations from data at multiple scales and locations using spherical wavelets and spectral graph partitioning. Our results show that when the training set is small, our algorithm significantly improves the approximation of shapes in a testing set over PCA, which tends to oversmooth data. PMID:16685992

Multiscale 3D shape analysis using spherical wavelets.

PubMed

Nain, Delphine; Haker, Steven; Bobick, Aaron; Tannenbaum, Allen R

2005-01-01

Shape priors attempt to represent biological variations within a population. When variations are global, Principal Component Analysis (PCA) can be used to learn major modes of variation, even from a limited training set. However, when significant local variations exist, PCA typically cannot represent such variations from a small training set. To address this issue, we present a novel algorithm that learns shape variations from data at multiple scales and locations using spherical wavelets and spectral graph partitioning. Our results show that when the training set is small, our algorithm significantly improves the approximation of shapes in a testing set over PCA, which tends to oversmooth data.

PCA3 noncoding RNA is involved in the control of prostate-cancer cell survival and modulates androgen receptor signaling

PubMed Central

2012-01-01

Background PCA3 is a non-coding RNA (ncRNA) that is highly expressed in prostate cancer (PCa) cells, but its functional role is unknown. To investigate its putative function in PCa biology, we used gene expression knockdown by small interference RNA, and also analyzed its involvement in androgen receptor (AR) signaling. Methods LNCaP and PC3 cells were used as in vitro models for these functional assays, and three different siRNA sequences were specifically designed to target PCA3 exon 4. Transfected cells were analyzed by real-time qRT-PCR and cell growth, viability, and apoptosis assays. Associations between PCA3 and the androgen-receptor (AR) signaling pathway were investigated by treating LNCaP cells with 100 nM dihydrotestosterone (DHT) and with its antagonist (flutamide), and analyzing the expression of some AR-modulated genes (TMPRSS2, NDRG1, GREB1, PSA, AR, FGF8, CdK1, CdK2 and PMEPA1). PCA3 expression levels were investigated in different cell compartments by using differential centrifugation and qRT-PCR. Results LNCaP siPCA3-transfected cells significantly inhibited cell growth and viability, and increased the proportion of cells in the sub G0/G1 phase of the cell cycle and the percentage of pyknotic nuclei, compared to those transfected with scramble siRNA (siSCr)-transfected cells. DHT-treated LNCaP cells induced a significant upregulation of PCA3 expression, which was reversed by flutamide. In siPCA3/LNCaP-transfected cells, the expression of AR target genes was downregulated compared to siSCr-transfected cells. The siPCA3 transfection also counteracted DHT stimulatory effects on the AR signaling cascade, significantly downregulating expression of the AR target gene. Analysis of PCA3 expression in different cell compartments provided evidence that the main functional roles of PCA3 occur in the nuclei and microsomal cell fractions. Conclusions Our findings suggest that the ncRNA PCA3 is involved in the control of PCa cell survival, in part through modulating AR signaling, which may raise new possibilities of using PCA3 knockdown as an additional therapeutic strategy for PCa control. PMID:23130941

Optimizing the clinical utility of PCA3 to diagnose prostate cancer in initial prostate biopsy.

PubMed

Rubio-Briones, Jose; Borque, Angel; Esteban, Luis M; Casanova, Juan; Fernandez-Serra, Antonio; Rubio, Luis; Casanova-Salas, Irene; Sanz, Gerardo; Domínguez-Escrig, Jose; Collado, Argimiro; Gómez-Ferrer, Alvaro; Iborra, Inmaculada; Ramírez-Backhaus, Miguel; Martínez, Francisco; Calatrava, Ana; Lopez-Guerrero, Jose A

2015-09-11

PCA3 has been included in a nomogram outperforming previous clinical models for the prediction of any prostate cancer (PCa) and high grade PCa (HGPCa) at the initial prostate biopsy (IBx). Our objective is to validate such IBx-specific PCA3-based nomogram. We also aim to optimize the use of this nomogram in clinical practice through the definition of risk groups. Independent external validation. Clinical and biopsy data from a contemporary cohort of 401 men with the same inclusion criteria to those used to build up the reference's nomogram in IBx. The predictive value of the nomogram was assessed by means of calibration curves and discrimination ability through the area under the curve (AUC). Clinical utility of the nomogram was analyzed by choosing thresholds points that minimize the overlapping between probability density functions (PDF) in PCa and no PCa and HGPCa and no HGPCa groups, and net benefit was assessed by decision curves. We detect 28% of PCa and 11 % of HGPCa in IBx, contrasting to the 46 and 20% at the reference series. Due to this, there is an overestimation of the nomogram probabilities shown in the calibration curve for PCa. The AUC values are 0.736 for PCa (C.I.95%:0.68-0.79) and 0.786 for HGPCa (C.I.95%:0.71-0.87) showing an adequate discrimination ability. PDF show differences in the distributions of nomogram probabilities in PCa and not PCa patient groups. A minimization of the overlapping between these curves confirms the threshold probability of harboring PCa >30 % proposed by Hansen is useful to indicate a IBx, but a cut-off > 40% could be better in series of opportunistic screening like ours. Similar results appear in HGPCa analysis. The decision curve also shows a net benefit of 6.31% for the threshold probability of 40%. PCA3 is an useful tool to select patients for IBx. Patients with a calculated probability of having PCa over 40% should be counseled to undergo an IBx if opportunistic screening is required.

Prostate health index and prostate cancer gene 3 score but not percent-free Prostate Specific Antigen have a predictive role in differentiating histological prostatitis from PCa and other nonneoplastic lesions (BPH and HG-PIN) at repeat biopsy.

PubMed

De Luca, Stefano; Passera, Roberto; Fiori, Cristian; Bollito, Enrico; Cappia, Susanna; Mario Scarpa, Roberto; Sottile, Antonino; Franco Randone, Donato; Porpiglia, Francesco

2015-10-01

To determine if prostate health index (PHI), prostate cancer antigen gene 3 (PCA3) score, and percentage of free prostate-specific antigen (%fPSA) may be used to differentiate asymptomatic acute and chronic prostatitis from prostate cancer (PCa), benign prostatic hyperplasia (BPH), and high-grade prostate intraepithelial neoplasia (HG-PIN) in patients with elevated PSA levels and negative findings on digital rectal examination at repeat biopsy (re-Bx). In this prospective study, 252 patients were enrolled, undergoing PHI, PCA3 score, and %fPSA assessments before re-Bx. We used 3 multivariate logistic regression models to test the PHI, PCA3 score, and %fPSA as risk factors for prostatitis vs. PCa, vs. BPH, and vs. HG-PIN. All the analyses were performed for the whole patient cohort and for the "gray zone" of PSA (4-10ng/ml) cohort (171 individuals). Of the 252 patients, 43 (17.1%) had diagnosis of PCa. The median PHI was significantly different between men with a negative biopsy and those with a positive biopsy (34.9 vs. 48.1, P<0.001), as for the PCA3 score (24 vs. 54, P<0.001) and %fPSA (11.8% vs. 15.8%, P = 0.012). The net benefit of using PCA3 and PHI to differentiate prostatitis and PCa was moderate, although it extended to a good range of threshold probabilities (40%-100%), whereas that from using %fPSA was negligible: this pattern was reported for the whole population as for the "gray zone" PSA cohort. In front of a good diagnostic performance of all the 3 biomarkers in distinguishing negative biopsy vs. positive biopsy, the clinical benefit of using the PCA3 score and PHI to estimate prostatitis vs. PCa was comparable. PHI was the only determinant for prostatitis vs. BPH, whereas no biomarkers could differentiate prostate inflammation from HG-PIN. Copyright © 2015 Elsevier Inc. All rights reserved.

Understanding of multigene test results among males undergoing germline testing for inherited prostate cancer: Implications for genetic counseling.

PubMed

Giri, Veda N; Obeid, Elias; Hegarty, Sarah E; Gross, Laura; Bealin, Lisa; Hyatt, Colette; Fang, Carolyn Y; Leader, Amy

2018-04-14

Genetic testing (GT) for prostate cancer (PCA) is rising, with limited insights regarding genetic counseling (GC) needs of males. Genetic Evaluation of Men (GEM) is a prospective multigene testing study for inherited PCA. Men undergoing GC were surveyed on knowledge of cancer risk and genetics (CRG) and understanding of personal GT results to identify GC needs. GEM participants with or high-risk for PCA were recruited. Pre-test GC was in-person, with video and handout, or via telehealth. Post-test disclosure was in-person, by phone, or via telehealth. Clinical and family history data were obtained from participant surveys and medical records. Participants completed measures of knowledge of CRG, literacy, and numeracy pre-test and post-test. Understanding of personal genetic results was assessed post-test. Factors associated with knowledge of CRG and understanding of personal genetic results were examined using multivariable linear regression or McNemar's test. Among 109 men who completed pre- and post-GT surveys, multivariable analysis revealed family history meeting hereditary cancer syndrome (HCS) criteria was significantly predictive of higher baseline knowledge (P = 0.040). Of 101 men who responded definitively regarding understanding of results, 13 incorrectly reported their result (McNemar's P < 0.001). Factors significantly associated with discordance between reported and actual results included having a variant of uncertain significance (VUS) (P < 0.001) and undergoing GC via pre-test video and post-test phone disclosure (P = 0.015). While meeting criteria for HCS was associated with higher knowledge of CRG, understanding of personal GT results was lacking among a subset of males with VUS. A more exploratory finding was lack of understanding of results among men who underwent GC utilizing video and phone. Studies optimizing GC strategies for males undergoing multigene testing for inherited PCA are warranted. © 2018 Wiley Periodicals, Inc.

2L-PCA: a two-level principal component analyzer for quantitative drug design and its applications.

PubMed

Du, Qi-Shi; Wang, Shu-Qing; Xie, Neng-Zhong; Wang, Qing-Yan; Huang, Ri-Bo; Chou, Kuo-Chen

2017-09-19

A two-level principal component predictor (2L-PCA) was proposed based on the principal component analysis (PCA) approach. It can be used to quantitatively analyze various compounds and peptides about their functions or potentials to become useful drugs. One level is for dealing with the physicochemical properties of drug molecules, while the other level is for dealing with their structural fragments. The predictor has the self-learning and feedback features to automatically improve its accuracy. It is anticipated that 2L-PCA will become a very useful tool for timely providing various useful clues during the process of drug development.

The burden of urinary incontinence and urinary bother among elderly prostate cancer survivors.

PubMed

Kopp, Ryan P; Marshall, Lynn M; Wang, Patty Y; Bauer, Douglas C; Barrett-Connor, Elizabeth; Parsons, J Kellogg

2013-10-01

Data describing urinary health in elderly, community-dwelling prostate cancer (PCa) survivors are limited. To elucidate the prevalence of lower urinary tract symptoms, urinary bother, and incontinence in elderly PCa survivors compared with peers without PCa. A cross-sectional analysis of 5990 participants in the Osteoporotic Fractures in Men Research Group, a cohort study of community-dwelling men ≥ 65 yr. We characterized urinary health using self-reported urinary incontinence and the American Urological Association Symptom Index (AUA-SI). We compared urinary health measures according to type of PCa treatment in men with PCa and men without PCa using multivariate log-binomial regression to generate prevalence ratios (PRs). At baseline, 706 men (12%) reported a history of PCa, with a mean time since diagnosis of 6.3 yr. Of these men, 426 (60%) reported urinary incontinence. In adjusted analyses, observation (PR: 2.11; 95% confidence interval [CI], 1.22-3.65; p=0.007), surgery (PR: 4.41; 95% CI, 3.79-5.13; p<0.0001), radiation therapy (PR: 1.49; 95% CI, 1.06-2.08; p=0.02), and androgen-deprivation therapy (ADT) (PR: 2.02; 95% CI, 1.31-3.13; p=0.002) were each associated with daily incontinence. Daily incontinence risk increased with time since diagnosis independently of age. Observation (PR: 1.33; 95% CI, 1.00-1.78; p=0.05), surgery (PR: 1.25; 95% CI, 1.10-1.42; p=0.0008), and ADT (PR: 1.50; 95% CI, 1.26-1.79; p<0.0001) were associated with increased AUA-SI bother scores. Cancer stage and use of adjuvant or salvage therapies were not available for analysis. Compared with their peers without PCa, elderly PCa survivors had a two-fold to five-fold greater prevalence of urinary incontinence, which rose with increasing survivorship duration. Observation, surgery, and ADT were each associated with increased urinary bother. These data suggest a substantially greater burden of urinary health problems among elderly PCa survivors than previously recognized. Copyright © 2013 European Association of Urology. Published by Elsevier B.V. All rights reserved.

MiR-145 detection in urinary extracellular vesicles increase diagnostic efficiency of prostate cancer based on hydrostatic filtration dialysis method.

PubMed

Xu, Yong; Qin, Sihua; An, Taixue; Tang, Yueting; Huang, Yiyao; Zheng, Lei

2017-07-01

Extracellular vesicles (EVs) can be detected in body fluids and may serve as disease biomarkers. Increasing evidence suggests that circulating miRNAs in serum and urine may be potential non-invasive biomarkers for prostate cancer (PCa). In the present study, we aimed to investigate whether hydrostatic filtration dialysis (HFD) is suitable for urinary EVs (UEVs) isolation and whether such reported PCa-related miRNAs can be detected in UEVs as PCa biomarkers. To analyze EVs miRNAs, we searched for an easy and economic method to enrich EVs from urine samples. We compared the efficiency of HFD method and conventional ultracentrifugation (UC) in isolating UEVs. Subsequently, UEVs were isolated from patients with PCa, patients with benign prostate hyperplasia (BPH) and healthy individuals. Differential expression of four PCa-related miRNAs (miR-572, miR-1290, miR-141, and miR-145) were measured in UEVs and paired serum EVs using SYBR Green-based quantitative reverse transcription-polymerase chain reaction (qRT-PCR). The overall performance of HFD was similar to UC. In miRNA yield, both HFD and UC can meet the needs of further analysis. The level of miR-145 in UEVs was significantly increased in patients with PCa compared with the patients with BPH (P = 0.018). In addition, significant increase was observed in miR-145 levels when patients with Gleason score ≥8 tumors compared with Gleason score ≤7 (P = 0.020). Receiver-operating characteristic curve (ROC) revealed that miR-145 in UEVs combined with serum PSA could differentiate PCa from BPH better than PSA alone (AUC 0.863 and AUC 0.805, respectively). In serum EVs, four miRNAs were significantly higher in patients with PCa than with BPH. HFD is appropriate for UEVs isolation and miRNA analysis when compared with conventional UC. miR-145 in UEVs is upregulated from PCa patients compared BPH patients and healthy controls. We suggest the potential use of UEVs miR-145 as a biomarker of PCa. © 2017 Wiley Periodicals, Inc.

Silibinin prevents prostate cancer cell-mediated differentiation of naïve fibroblasts into cancer-associated fibroblast phenotype by targeting TGF β2.

PubMed

Ting, Harold J; Deep, Gagan; Jain, Anil K; Cimic, Adela; Sirintrapun, Joseph; Romero, Lina M; Cramer, Scott D; Agarwal, Chapla; Agarwal, Rajesh

2015-09-01

Tumor microenvironment (TM) is an essential element in prostate cancer (PCA), offering unique opportunities for its prevention. TM includes naïve fibroblasts that are recruited by nascent neoplastic lesion and altered into 'cancer-associated fibroblasts' (CAFs) that promote PCA. A better understanding and targeting of interaction between PCA cells and fibroblasts and inhibiting CAF phenotype through non-toxic agents are novel approaches to prevent PCA progression. One well-studied cancer chemopreventive agent is silibinin, and thus, we examined its efficacy against PCA cells-mediated differentiation of naïve fibroblasts into a myofibroblastic-phenotype similar to that found in CAFs. Silibinin's direct inhibitory effect on the phenotype of CAFs derived directly from PCA patients was also assessed. Human prostate stromal cells (PrSCs) exposed to control conditioned media (CCM) from human PCA PC3 cells showed more invasiveness, with increased alpha-smooth muscle actin (α-SMA) and vimentin expression, and differentiation into a phenotype we identified in CAFs. Importantly, silibinin (at physiologically achievable concentrations) inhibited α-SMA expression and invasiveness in differentiated fibroblasts and prostate CAFs directly, as well as indirectly by targeting PCA cells. The observed increase in α-SMA and CAF-like phenotype was transforming growth factor (TGF) β2 dependent, which was strongly inhibited by silibinin. Furthermore, induction of α-SMA and CAF phenotype by CCM were also strongly inhibited by a TGFβ2-neutralizing antibody. The inhibitory effect of silibinin on TGFβ2 expression and CAF-like biomarkers was also observed in PC3 tumors. Together, these findings highlight the potential usefulness of silibinin in PCA prevention through targeting the CAF phenotype in the prostate TM. © 2014 Wiley Periodicals, Inc.

Epileptic seizure detection in EEG signal with GModPCA and support vector machine.

PubMed

Jaiswal, Abeg Kumar; Banka, Haider

2017-01-01

Epilepsy is one of the most common neurological disorders caused by recurrent seizures. Electroencephalograms (EEGs) record neural activity and can detect epilepsy. Visual inspection of an EEG signal for epileptic seizure detection is a time-consuming process and may lead to human error; therefore, recently, a number of automated seizure detection frameworks were proposed to replace these traditional methods. Feature extraction and classification are two important steps in these procedures. Feature extraction focuses on finding the informative features that could be used for classification and correct decision-making. Therefore, proposing effective feature extraction techniques for seizure detection is of great significance. Principal Component Analysis (PCA) is a dimensionality reduction technique used in different fields of pattern recognition including EEG signal classification. Global modular PCA (GModPCA) is a variation of PCA. In this paper, an effective framework with GModPCA and Support Vector Machine (SVM) is presented for epileptic seizure detection in EEG signals. The feature extraction is performed with GModPCA, whereas SVM trained with radial basis function kernel performed the classification between seizure and nonseizure EEG signals. Seven different experimental cases were conducted on the benchmark epilepsy EEG dataset. The system performance was evaluated using 10-fold cross-validation. In addition, we prove analytically that GModPCA has less time and space complexities as compared to PCA. The experimental results show that EEG signals have strong inter-sub-pattern correlations. GModPCA and SVM have been able to achieve 100% accuracy for the classification between normal and epileptic signals. Along with this, seven different experimental cases were tested. The classification results of the proposed approach were better than were compared the results of some of the existing methods proposed in literature. It is also found that the time and space complexities of GModPCA are less as compared to PCA. This study suggests that GModPCA and SVM could be used for automated epileptic seizure detection in EEG signal.

Gabor-based kernel PCA with fractional power polynomial models for face recognition.

PubMed

Liu, Chengjun

2004-05-01

This paper presents a novel Gabor-based kernel Principal Component Analysis (PCA) method by integrating the Gabor wavelet representation of face images and the kernel PCA method for face recognition. Gabor wavelets first derive desirable facial features characterized by spatial frequency, spatial locality, and orientation selectivity to cope with the variations due to illumination and facial expression changes. The kernel PCA method is then extended to include fractional power polynomial models for enhanced face recognition performance. A fractional power polynomial, however, does not necessarily define a kernel function, as it might not define a positive semidefinite Gram matrix. Note that the sigmoid kernels, one of the three classes of widely used kernel functions (polynomial kernels, Gaussian kernels, and sigmoid kernels), do not actually define a positive semidefinite Gram matrix either. Nevertheless, the sigmoid kernels have been successfully used in practice, such as in building support vector machines. In order to derive real kernel PCA features, we apply only those kernel PCA eigenvectors that are associated with positive eigenvalues. The feasibility of the Gabor-based kernel PCA method with fractional power polynomial models has been successfully tested on both frontal and pose-angled face recognition, using two data sets from the FERET database and the CMU PIE database, respectively. The FERET data set contains 600 frontal face images of 200 subjects, while the PIE data set consists of 680 images across five poses (left and right profiles, left and right half profiles, and frontal view) with two different facial expressions (neutral and smiling) of 68 subjects. The effectiveness of the Gabor-based kernel PCA method with fractional power polynomial models is shown in terms of both absolute performance indices and comparative performance against the PCA method, the kernel PCA method with polynomial kernels, the kernel PCA method with fractional power polynomial models, the Gabor wavelet-based PCA method, and the Gabor wavelet-based kernel PCA method with polynomial kernels.

Multivariate Analysis of Fruit Antioxidant Activities of Blackberry Treated with 1-Methylcyclopropene or Vacuum Precooling

PubMed Central

Li, Jian; Ma, Guowei; Ma, Lin; Bao, Xiaolin; Li, Liping; Zhao, Qian

2018-01-01

Effects of 1-methylcyclopropene (1-MCP) and vacuum precooling on quality and antioxidant properties of blackberries (Rubus spp.) were evaluated using one-way analysis of variance, principal component analysis (PCA), partial least squares (PLS), and path analysis. Results showed that the activities of antioxidant enzymes were enhanced by both 1-MCP treatment and vacuum precooling. PCA could discriminate 1-MCP treated fruit and the vacuum precooled fruit and showed that the radical-scavenging activities in vacuum precooled fruit were higher than those in 1-MCP treated fruit. The scores of PCA showed that H2O2 content was the most important variables of blackberry fruit. PLSR results showed that peroxidase (POD) activity negatively correlated with H2O2 content. The results of path coefficient analysis indicated that glutathione (GSH) also had an indirect effect on H2O2 content. PMID:29487622

Application of principal component analysis (PCA) as a sensory assessment tool for fermented food products.

PubMed

Ghosh, Debasree; Chattopadhyay, Parimal

2012-06-01

The objective of the work was to use the method of quantitative descriptive analysis (QDA) to describe the sensory attributes of the fermented food products prepared with the incorporation of lactic cultures. Panellists were selected and trained to evaluate various attributes specially color and appearance, body texture, flavor, overall acceptability and acidity of the fermented food products like cow milk curd and soymilk curd, idli, sauerkraut and probiotic ice cream. Principal component analysis (PCA) identified the six significant principal components that accounted for more than 90% of the variance in the sensory attribute data. Overall product quality was modelled as a function of principal components using multiple least squares regression (R (2) = 0.8). The result from PCA was statistically analyzed by analysis of variance (ANOVA). These findings demonstrate the utility of quantitative descriptive analysis for identifying and measuring the fermented food product attributes that are important for consumer acceptability.

Neurophysiological differences between patients clinically at high risk for schizophrenia and neurotypical controls--first steps in development of a biomarker.

PubMed

Duffy, Frank H; D'Angelo, Eugene; Rotenberg, Alexander; Gonzalez-Heydrich, Joseph

2015-11-02

Schizophrenia is a severe, disabling and prevalent mental disorder without cure and with a variable, incomplete pharmacotherapeutic response. Prior to onset in adolescence or young adulthood a prodromal period of abnormal symptoms lasting weeks to years has been identified and operationalized as clinically high risk (CHR) for schizophrenia. However, only a minority of subjects prospectively identified with CHR convert to schizophrenia, thereby limiting enthusiasm for early intervention(s). This study utilized objective resting electroencephalogram (EEG) quantification to determine whether CHR constitutes a cohesive entity and an evoked potential to assess CHR cortical auditory processing. This study constitutes an EEG-based quantitative neurophysiological comparison between two unmedicated subject groups: 35 neurotypical controls (CON) and 22 CHR patients. After artifact management, principal component analysis (PCA) identified EEG spectral and spectral coherence factors described by associated loading patterns. Discriminant function analysis (DFA) determined factors' discrimination success between subjects in the CON and CHR groups. Loading patterns on DFA-selected factors described CHR-specific spectral and coherence differences when compared to controls. The frequency modulated auditory evoked response (FMAER) explored functional CON-CHR differences within the superior temporal gyri. Variable reduction by PCA identified 40 coherence-based factors explaining 77.8% of the total variance and 40 spectral factors explaining 95.9% of the variance. DFA demonstrated significant CON-CHR group difference (P <0.00001) and successful jackknifed subject classification (CON, 85.7%; CHR, 86.4% correct). The population distribution plotted along the canonical discriminant variable was clearly bimodal. Coherence factors delineated loading patterns of altered connectivity primarily involving the bilateral posterior temporal electrodes. However, FMAER analysis showed no CON-CHR group differences. CHR subjects form a cohesive group, significantly separable from CON subjects by EEG-derived indices. Symptoms of CHR may relate to altered connectivity with the posterior temporal regions but not to primary auditory processing abnormalities within these regions.

Prostate specific antigen (PSA) kinetic as a prognostic factor in metastatic prostate cancer receiving androgen deprivation therapy: systematic review and meta-analysis.

PubMed

Afriansyah, Andika; Hamid, Agus Rizal Ardy Hariandy; Mochtar, Chaidir Arif; Umbas, Rainy

2018-01-01

Aim: Metastatic prostate cancer (mPCa) has a poor outcome with median survival of two to five years. The use of androgen deprivation therapy (ADT) is a gold standard in management of this stage.  Aim of this study is to analyze the prognostic value of PSA kinetics of patient treated with hormonal therapy related to survival from several published studies Method: Systematic review and meta-analysis was performed using literature searching in the electronic databases of MEDLINE, Science Direct, and Cochrane Library. Inclusion criteria were mPCa receiving ADT, a study analyzing Progression Free Survival (PFS), Overall Survival (OS), or Cancer Specific Survival (CSS) and prognostic factor of survival related to PSA kinetics (initial PSA, PSA nadir, and time to achieve nadir (TTN)). The exclusion criteria were metastatic castration resistant of prostate cancer (mCRPC) and non-metastatic disease. Generic inverse variance method was used to combine hazard ratio (HR) within the studies. Meta-analysis was performed using Review Manager 5.2 and a p-value <0.05 was considered statistically significant. Results: We found 873 citations throughout database searching with 17 studies were consistent with inclusion criteria. However, just 10 studies were analyzed in the quantitative analysis. Most of the studies had a good methodological quality based on Ottawa Scale. No significant association between initial PSA and PFS. In addition, there was no association between initial PSA and CSS/ OS. We found association of reduced PFS (HR 2.22; 95% CI 1.82 to 2.70) and OS/ CSS (HR 3.31; 95% CI 2.01-5.43) of patient with high PSA nadir. Shorter TTN was correlated with poor result of survival either PFS (HR 2.41; 95% CI 1.19 - 4.86) or CSS/ OS (HR 1.80; 95%CI  1.42 - 2.30) Conclusion: Initial PSA before starting ADT do not associated with survival in mPCa.  There is association of PSA nadir and TTN with survival.

Prostate specific antigen (PSA) kinetic as a prognostic factor in metastatic prostate cancer receiving androgen deprivation therapy: systematic review and meta-analysis

PubMed Central

Afriansyah, Andika; Hamid, Agus Rizal Ardy Hariandy; Mochtar, Chaidir Arif; Umbas, Rainy

2018-01-01

Aim: Metastatic prostate cancer (mPCa) has a poor outcome with median survival of two to five years. The use of androgen deprivation therapy (ADT) is a gold standard in management of this stage.  Aim of this study is to analyze the prognostic value of PSA kinetics of patient treated with hormonal therapy related to survival from several published studies Method: Systematic review and meta-analysis was performed using literature searching in the electronic databases of MEDLINE, Science Direct, and Cochrane Library. Inclusion criteria were mPCa receiving ADT, a study analyzing Progression Free Survival (PFS), Overall Survival (OS), or Cancer Specific Survival (CSS) and prognostic factor of survival related to PSA kinetics (initial PSA, PSA nadir, and time to achieve nadir (TTN)). The exclusion criteria were metastatic castration resistant of prostate cancer (mCRPC) and non-metastatic disease. Generic inverse variance method was used to combine hazard ratio (HR) within the studies. Meta-analysis was performed using Review Manager 5.2 and a p-value <0.05 was considered statistically significant. Results: We found 873 citations throughout database searching with 17 studies were consistent with inclusion criteria. However, just 10 studies were analyzed in the quantitative analysis. Most of the studies had a good methodological quality based on Ottawa Scale. No significant association between initial PSA and PFS. In addition, there was no association between initial PSA and CSS/ OS. We found association of reduced PFS (HR 2.22; 95% CI 1.82 to 2.70) and OS/ CSS (HR 3.31; 95% CI 2.01-5.43) of patient with high PSA nadir. Shorter TTN was correlated with poor result of survival either PFS (HR 2.41; 95% CI 1.19 – 4.86) or CSS/ OS (HR 1.80; 95%CI  1.42 – 2.30) Conclusion: Initial PSA before starting ADT do not associated with survival in mPCa.  There is association of PSA nadir and TTN with survival PMID:29904592

Fixed Eigenvector Analysis of Thermographic NDE Data

NASA Technical Reports Server (NTRS)

Cramer, K. Elliott; Winfree, William P.

2011-01-01

Principal Component Analysis (PCA) has been shown effective for reducing thermographic NDE data. This paper will discuss an alternative method of analysis that has been developed where a predetermined set of eigenvectors is used to process the thermal data from both reinforced carbon-carbon (RCC) and graphiteepoxy honeycomb materials. These eigenvectors can be generated either from an analytic model of the thermal response of the material system under examination, or from a large set of experimental data. This paper provides the details of the analytic model, an overview of the PCA process, as well as a quantitative signal-to-noise comparison of the results of performing both conventional PCA and fixed eigenvector analysis on thermographic data from two specimens, one Reinforced Carbon-Carbon with flat bottom holes and the second a sandwich construction with graphite-epoxy face sheets and aluminum honeycomb core.

Pectus Carinatum Evaluation Questionnaire (PCEQ): a novel tool to improve the follow-up in patients treated with brace compression.

PubMed

Pessanha, Inês; Severo, Milton; Correia-Pinto, Jorge; Estevão-Costa, José; Henriques-Coelho, Tiago

2016-03-01

A questionnaire (Pectus Carinatum Evaluation Questionnaire, PCEQ) was developed to be applied in follow-up of patients with Pectus Carinatum (PC). After validation of the PCEQ, we aimed to quantify the compliance to brace compression and to assess factors that could influence this treatment in patients with PC. From July 2008 to July 2014, 56 patients with PC were treated with the Calgary Protocol of compressive bracing at Paediatric Surgery Department of Hospital São João. Forty patients (71%) completed the questionnaire. The PCEQ was divided into four sections: (i) compliance; (ii) symptoms; (iii) social influence; (iv) activities. For the validation process of the PCEQ, principal components analysis (PCA), orthogonal varimax or oblimin rotation and Cronbach's α coefficient were used. To evaluate the association between compliance and other sections of the questionnaire, we estimated the Pearson's correlation between compliance factor scores ('Compliance Days' and 'Compliance Hours') and the final score of each new questionnaire component identified by PCA ('Chest Pain', 'Dyspnoea', 'Back Pain', 'Parents' Influence', 'Friends' Influence', 'Activities', 'Time To Compliance'). For the sections 'Symptoms', 'Social Influence' and 'Activities', we estimated final scores as the sum of the questions that constitute each component. For the section 'Compliance', the factor scores were estimated by the regression method. After PCA analysis, the PCEQ found nine different components with high reliability. When analysing the compliance of our study group, the final score for 'Activities' revealed a significant correlation with the factor score for 'Compliance Hours' (r = 0.382, P = 0.015). The final score for 'Time To Compliance' showed a significant correlation with both factor scores for 'Compliance Hours' (r = -0.765, P < 0.001) and 'Compliance Days' (r = -0.345, P < 0.029). The PCEQ seems to be an important tool to follow up patients with PC treated by brace compression. Practical steps, such as developing a tight schedule in the early follow-up period or applying the PCEQ in first visits after initiating brace therapy, can be taken in order to increase compliance with brace therapy and improve the quality of life. © The Author 2015. Published by Oxford University Press on behalf of the European Association for Cardio-Thoracic Surgery. All rights reserved.

L-dopa decarboxylase (DDC) gene expression is related to outcome in patients with prostate cancer.

PubMed

Koutalellis, Georgios; Stravodimos, Konstantinos; Avgeris, Margaritis; Mavridis, Konstantinos; Scorilas, Andreas; Lazaris, Andreas; Constantinides, Constantinos

2012-09-01

What's known on the subject? and What does the study add? L-dopa decarboxylase (DDC) has been documented as a novel co-activator of androgen receptor transcriptional activity. Recently, it was shown that DDC gene expression is significantly higher in patients with PCa than in those with BPH. In the present study, there was a significant association between the DDC gene expression levels and the pathological stage and Gleason score of patients with prostate cancer (PCa). Moreover, DDC expression was shown to be an unfavourable prognostic marker of biochemical recurrence and disease-free survival in patients with PCa treated by radical prostatectomy. To determine whether L-dopa decarboxylase gene (DDC) expression levels in patients with prostate cancer (PCa) correlate to biochemical recurrence and disease prognosis after radical prostatectomy (RP). The present study consisted of 56 samples with confirmed malignancy from patients with PCa who had undergone RP at a single tertiary academic centre. Total RNA was isolated from tissue specimens and a SYBR Green fluorescence-based quantitative real-time polymerase chain reaction methodology was developed for the determination of DDC mRNA expression levels of the tested tissues. Follow-up time ranged between 1.0 and 62.0 months (mean ± SE, 28.6 ± 2.1 month; median, 31.5 months). Time to biochemical recurrence was defined as the interval between the surgery and the measurement of two consecutive values of prostate-specific antigen (PSA) ≥0.2 ng/mL. DDC expression levels were found to be positively correlated with the tumour-node-metastasis stage (P = 0.021) and Gleason score (P = 0.036) of the patients with PCa. Patients with PCa with raised DDC expression levels run a significantly higher risk of biochemical recurrence after RP, as indicated by Cox proportional regression analysis (P = 0.021). Multivariate Cox proportional regression models revealed the preoperative PSA-, age- and digital rectal examination-independent prognostic value of DDC expression for the prediction of disease-free survival (DFS) among patients with PCa (P = 0.036). Kaplan-Meier survival analysis confirms the significantly shorter DFS after RP of PCa with higher DDC expression levels (P = 0.015). This is the first study indicating the potential of DDC expression as a novel prognostic biomarker in patients with PCa who have undergone RP. For further evaluation and clinical application of the findings of the present study, a direct analysis of mRNA and/or its protein expression level in preoperative biopsy, blood serum and urine should be conducted. © 2012 BJU INTERNATIONAL.

An in vitro investigation on friction generated by ceramic brackets.

PubMed

Tecco, Simona; Teté, Stefano; Festa, Mario; Festa, Felice

2010-01-01

To compare friction (F) of conventional and ceramic brackets (0.022-inch slot) using a model that tests the sliding of the archwire through 10 aligned brackets. Polycrystalline alumina brackets (PCAs), PCA brackets with a stainless steel slot (PCA-M), and monocrystalline sapphire brackets (MCS) were tested under elastic ligatures using various archwires in dry and wet (saliva) states. Conventional stainless steel brackets were used as controls. In both dry and wet states, PCA and MCS brackets expressed a statistically significant higher F value with respect to stainless steel and PCA-M brackets when combined with the rectangular archwires (P<.01). PCA brackets showed significantly higher friction than MCS brackets (P<.01) when coupled with 0.014 x 0.025-inch nickel-titanium (Ni-Ti) archwire. SEM analysis showed differences in the surfaces among stainless steel, MCS, PCA-M, and PCA brackets. In the wet state, the mean F values were generally higher than in the dry state. PCA brackets showed significantly higher F than MCS brackets only when combined with 0.014 x 0.025-inch Ni-Ti archwires. Thus, in this study, a 10 aligned-brackets study model showed similar results when compared to a single bracket system except for friction level with 0.014 × 0.025-inch Ni-Ti archwires. © 2011 BY QUINTESSENCE PUBLISHING CO, INC.

Perturbational formulation of principal component analysis in molecular dynamics simulation.

PubMed

Koyama, Yohei M; Kobayashi, Tetsuya J; Tomoda, Shuji; Ueda, Hiroki R

2008-10-01

Conformational fluctuations of a molecule are important to its function since such intrinsic fluctuations enable the molecule to respond to the external environmental perturbations. For extracting large conformational fluctuations, which predict the primary conformational change by the perturbation, principal component analysis (PCA) has been used in molecular dynamics simulations. However, several versions of PCA, such as Cartesian coordinate PCA and dihedral angle PCA (dPCA), are limited to use with molecules with a single dominant state or proteins where the dihedral angle represents an important internal coordinate. Other PCAs with general applicability, such as the PCA using pairwise atomic distances, do not represent the physical meaning clearly. Therefore, a formulation that provides general applicability and clearly represents the physical meaning is yet to be developed. For developing such a formulation, we consider the conformational distribution change by the perturbation with arbitrary linearly independent perturbation functions. Within the second order approximation of the Kullback-Leibler divergence by the perturbation, the PCA can be naturally interpreted as a method for (1) decomposing a given perturbation into perturbations that independently contribute to the conformational distribution change or (2) successively finding the perturbation that induces the largest conformational distribution change. In this perturbational formulation of PCA, (i) the eigenvalue measures the Kullback-Leibler divergence from the unperturbed to perturbed distributions, (ii) the eigenvector identifies the combination of the perturbation functions, and (iii) the principal component determines the probability change induced by the perturbation. Based on this formulation, we propose a PCA using potential energy terms, and we designate it as potential energy PCA (PEPCA). The PEPCA provides both general applicability and clear physical meaning. For demonstrating its power, we apply the PEPCA to an alanine dipeptide molecule in vacuum as a minimal model of a nonsingle dominant conformational biomolecule. The first and second principal components clearly characterize two stable states and the transition state between them. Positive and negative components with larger absolute values of the first and second eigenvectors identify the electrostatic interactions, which stabilize or destabilize each stable state and the transition state. Our result therefore indicates that PCA can be applied, by carefully selecting the perturbation functions, not only to identify the molecular conformational fluctuation but also to predict the conformational distribution change by the perturbation beyond the limitation of the previous methods.

Perturbational formulation of principal component analysis in molecular dynamics simulation

NASA Astrophysics Data System (ADS)

Koyama, Yohei M.; Kobayashi, Tetsuya J.; Tomoda, Shuji; Ueda, Hiroki R.

2008-10-01

Conformational fluctuations of a molecule are important to its function since such intrinsic fluctuations enable the molecule to respond to the external environmental perturbations. For extracting large conformational fluctuations, which predict the primary conformational change by the perturbation, principal component analysis (PCA) has been used in molecular dynamics simulations. However, several versions of PCA, such as Cartesian coordinate PCA and dihedral angle PCA (dPCA), are limited to use with molecules with a single dominant state or proteins where the dihedral angle represents an important internal coordinate. Other PCAs with general applicability, such as the PCA using pairwise atomic distances, do not represent the physical meaning clearly. Therefore, a formulation that provides general applicability and clearly represents the physical meaning is yet to be developed. For developing such a formulation, we consider the conformational distribution change by the perturbation with arbitrary linearly independent perturbation functions. Within the second order approximation of the Kullback-Leibler divergence by the perturbation, the PCA can be naturally interpreted as a method for (1) decomposing a given perturbation into perturbations that independently contribute to the conformational distribution change or (2) successively finding the perturbation that induces the largest conformational distribution change. In this perturbational formulation of PCA, (i) the eigenvalue measures the Kullback-Leibler divergence from the unperturbed to perturbed distributions, (ii) the eigenvector identifies the combination of the perturbation functions, and (iii) the principal component determines the probability change induced by the perturbation. Based on this formulation, we propose a PCA using potential energy terms, and we designate it as potential energy PCA (PEPCA). The PEPCA provides both general applicability and clear physical meaning. For demonstrating its power, we apply the PEPCA to an alanine dipeptide molecule in vacuum as a minimal model of a nonsingle dominant conformational biomolecule. The first and second principal components clearly characterize two stable states and the transition state between them. Positive and negative components with larger absolute values of the first and second eigenvectors identify the electrostatic interactions, which stabilize or destabilize each stable state and the transition state. Our result therefore indicates that PCA can be applied, by carefully selecting the perturbation functions, not only to identify the molecular conformational fluctuation but also to predict the conformational distribution change by the perturbation beyond the limitation of the previous methods.

Elevated YKL40 is associated with advanced prostate cancer (PCa) and positively regulates invasion and migration of PCa cells

PubMed Central

Jeet, Varinder; Tevz, Gregor; Lehman, Melanie; Hollier, Brett; Nelson, Colleen

2014-01-01

Chitinase 3-like 1 (CHI3L1 or YKL40) is a secreted glycoprotein highly expressed in tumours from patients with advanced stage cancers, including prostate cancer (PCa). The exact function of YKL40 is poorly understood, but it has been shown to play an important role in promoting tumour angiogenesis and metastasis. The therapeutic value and biological function of YKL40 are unknown in PCa. The objective of this study was to examine the expression and function of YKL40 in PCa. Gene expression analysis demonstrated that YKL40 was highly expressed in metastatic PCa cells when compared with less invasive and normal prostate epithelial cell lines. In addition, the expression was primarily limited to androgen receptor-positive cell lines. Evaluation of YKL40 tissue expression in PCa patients showed a progressive increase in patients with aggressive disease when compared with those with less aggressive cancers and normal controls. Treatment of LNCaP and C4-2B cells with androgens increased YKL40 expression, whereas treatment with an anti-androgen agent decreased the gene expression of YKL40 in androgen-sensitive LNCaP cells. Furthermore, knockdown of YKL40 significantly decreased invasion and migration of PCa cells, whereas overexpression rendered them more invasive and migratory, which was commensurate with an enhancement in the anchorage-independent growth of cells. To our knowledge, this study characterises the role of YKL40 for the first time in PCa. Together, these results suggest that YKL40 plays an important role in PCa progression and thus inhibition of YKL40 may be a potential therapeutic strategy for the treatment of PCa. PMID:24981110

Elevated YKL40 is associated with advanced prostate cancer (PCa) and positively regulates invasion and migration of PCa cells.

PubMed

Jeet, Varinder; Tevz, Gregor; Lehman, Melanie; Hollier, Brett; Nelson, Colleen

2014-10-01

Chitinase 3-like 1 (CHI3L1 or YKL40) is a secreted glycoprotein highly expressed in tumours from patients with advanced stage cancers, including prostate cancer (PCa). The exact function of YKL40 is poorly understood, but it has been shown to play an important role in promoting tumour angiogenesis and metastasis. The therapeutic value and biological function of YKL40 are unknown in PCa. The objective of this study was to examine the expression and function of YKL40 in PCa. Gene expression analysis demonstrated that YKL40 was highly expressed in metastatic PCa cells when compared with less invasive and normal prostate epithelial cell lines. In addition, the expression was primarily limited to androgen receptor-positive cell lines. Evaluation of YKL40 tissue expression in PCa patients showed a progressive increase in patients with aggressive disease when compared with those with less aggressive cancers and normal controls. Treatment of LNCaP and C4-2B cells with androgens increased YKL40 expression, whereas treatment with an anti-androgen agent decreased the gene expression of YKL40 in androgen-sensitive LNCaP cells. Furthermore, knockdown of YKL40 significantly decreased invasion and migration of PCa cells, whereas overexpression rendered them more invasive and migratory, which was commensurate with an enhancement in the anchorage-independent growth of cells. To our knowledge, this study characterises the role of YKL40 for the first time in PCa. Together, these results suggest that YKL40 plays an important role in PCa progression and thus inhibition of YKL40 may be a potential therapeutic strategy for the treatment of PCa. © 2014 The authors.

Biotransformation of ferulic acid to protocatechuic acid by Corynebacterium glutamicum ATCC 21420 engineered to express vanillate O-demethylase.

PubMed

Okai, Naoko; Masuda, Takaya; Takeshima, Yasunobu; Tanaka, Kosei; Yoshida, Ken-Ichi; Miyamoto, Masanori; Ogino, Chiaki; Kondo, Akihiko

2017-12-01

Ferulic acid (4-hydroxy-3-methoxycinnamic acid, FA) is a lignin-derived phenolic compound abundant in plant biomass. The utilization of FA and its conversion to valuable compounds is desired. Protocatechuic acid (3,4-dihydroxybenzoic acid, PCA) is a precursor of polymers and plastics and a constituent of food. A microbial conversion system to produce PCA from FA was developed in this study using a PCA-producing strain of Corynebacterium glutamicum F (ATCC 21420). C. glutamicum strain F grown at 30 °C for 48 h utilized 2 mM each of FA and vanillic acid (4-hydroxy-3-methoxybenzoic acid, VA) to produce PCA, which was secreted into the medium. FA may be catabolized by C. glutamicum through proposed (I) non-β-oxidative, CoA-dependent or (II) β-oxidative, CoA-dependent phenylpropanoid pathways. The conversion of VA to PCA is the last step in each pathway. Therefore, the vanillate O-demethylase gene (vanAB) from Corynebacterium efficiens NBRC 100395 was expressed in C. glutamicum F (designated strain FVan) cultured at 30 °C in AF medium containing FA. Strain C. glutamicum FVan converted 4.57 ± 0.07 mM of FA into 2.87 ± 0.01 mM PCA after 48 h with yields of 62.8% (mol/mol), and 6.91 mM (1064 mg/L) of PCA was produced from 16.0 mM of FA after 12 h of fed-batch biotransformation. Genomic analysis of C. glutamicum ATCC 21420 revealed that the PCA-utilization genes (pca cluster) were conserved in strain ATCC 21420 and that mutations were present in the PCA importer gene pcaK.

Assessment of the Eutrophication-Related Environmental Parameters in Two Mediterranean Lakes by Integrating Statistical Techniques and Self-Organizing Maps.

PubMed

Hadjisolomou, Ekaterini; Stefanidis, Konstantinos; Papatheodorou, George; Papastergiadou, Evanthia

2018-03-19

During the last decades, Mediterranean freshwater ecosystems, especially lakes, have been under severe pressure due to increasing eutrophication and water quality deterioration. In this article, we compared the effectiveness of different data analysis methods by assessing the contribution of environmental parameters to eutrophication processes. For this purpose, principal components analysis (PCA), cluster analysis, and a self-organizing map (SOM) were applied, using water quality data from two transboundary lakes of North Greece. SOM is considered as an advanced and powerful data analysis tool because of its ability to represent complex and nonlinear relationships among multivariate data sets. The results of PCA and cluster analysis agreed with the SOM results, although the latter provided more information because of the visualization abilities regarding the parameters' relationships. Besides nutrients that were found to be a key factor for controlling chlorophyll-a (Chl - a), water temperature was related positively with algal production, while the Secchi disk depth parameter was found to be highly important and negatively related toeutrophic conditions. In general, the SOM results were more specific and allowed direct associations between the water quality variables. Our work showed that SOMs can be used effectively in limnological studies to produce robust and interpretable results, aiding scientists and managers to cope with environmental problems such as eutrophication.

A genetic variant in SLC28A3, rs56350726, is associated with progression to castration-resistant prostate cancer in a Korean population with metastatic prostate cancer.

PubMed

Jo, Jung Ku; Oh, Jong Jin; Kim, Yong Tae; Moon, Hong Sang; Choi, Hong Yong; Park, Seunghyun; Ho, Jin-Nyoung; Yoon, Sungroh; Park, Hae Young; Byun, Seok-Soo

2017-11-14

Genetic variation which related with progression to castration-resistant prostate cancer (CRPC) during androgen-deprivation therapy (ADT) has not been elucidated in patients with metastatic prostate cancer (mPCa). Therefore, we assessed the association between genetic variats in mPCa and progession to CRPC. Analysis of exome genotypes revealed that 42 SNPs were significantly associated with mPCa. The top five polymorphisms were statistically significantly associated with metastatic disease. In addition, one of these SNPs, rs56350726, was significantly associated with time to CRPC in Kaplan-Meier analysis (Log-rank test, p = 0.011). In multivariable Cox regression, rs56350726 was strongly associated with progression to CRPC (HR = 4.172 95% CI = 1.223-14.239, p = 0.023). We assessed genetic variation among 1000 patients with PCa with or without metastasis, using 242,221 single nucleotide polymorphisms (SNPs) on the custom HumanExome BeadChip v1.0 (Illuminam Inc.). We analyzed the time to CRPC in 110 of the 1000 patients who were treated with ADT. Genetic data were analyzed using unconditional logistic regression and odds ratios calculated as estimates of relative risk of metastasis. We identified SNPs associated with metastasis and analyzed the relationship between these SNPs and time to CRPC in mPCa. Based on a genetic variation, the five top SNPs were observed to associate with mPCa. And one (SLC28A3, rs56350726) of five SNP was found the association with the progression to CRPC in patients with mPCa.

Cluster analysis of commercial samples of Bauhinia spp. using HPLC-UV/PDA and MCR-ALS/PCA without peak alignment procedure.

PubMed

Ardila, Jorge Armando; Funari, Cristiano Soleo; Andrade, André Marques; Cavalheiro, Alberto José; Carneiro, Renato Lajarim

2015-01-01

Bauhinia forficata Link. is recognised by the Brazilian Health Ministry as a treatment of hypoglycemia and diabetes. Analytical methods are useful to assess the plant identity due the similarities found in plants from Bauhinia spp. HPLC-UV/PDA in combination with chemometric tools is an alternative widely used and suitable for authentication of plant material, however, the shifts of retention times for similar compounds in different samples is a problem. To perform comparisons between the authentic medicinal plant (Bauhinia forficata Link.) and samples commercially available in drugstores claiming to be "Bauhinia spp. to treat diabetes" and to evaluate the performance of multivariate curve resolution - alternating least squares (MCR-ALS) associated to principal component analysis (PCA) when compared to pure PCA. HPLC-UV/PDA data obtained from extracts of leaves were evaluated employing a combination of MCR-ALS and PCA, which allowed the use of the full chromatographic and spectrometric information without the need of peak alignment procedures. The use of MCR-ALS/PCA showed better results than the conventional PCA using only one wavelength. Only two of nine commercial samples presented characteristics similar to the authentic Bauhinia forficata spp., considering the full HPLC-UV/PDA data. The combination of MCR-ALS and PCA is very useful when applied to a group of samples where a general alignment procedure could not be applied due to the different chromatographic profiles. This work also demonstrates the need of more strict control from the health authorities regarding herbal products available on the market. Copyright © 2015 John Wiley & Sons, Ltd.

Pattern identification in time-course gene expression data with the CoGAPS matrix factorization.

PubMed

Fertig, Elana J; Stein-O'Brien, Genevieve; Jaffe, Andrew; Colantuoni, Carlo

2014-01-01

Patterns in time-course gene expression data can represent the biological processes that are active over the measured time period. However, the orthogonality constraint in standard pattern-finding algorithms, including notably principal components analysis (PCA), confounds expression changes resulting from simultaneous, non-orthogonal biological processes. Previously, we have shown that Markov chain Monte Carlo nonnegative matrix factorization algorithms are particularly adept at distinguishing such concurrent patterns. One such matrix factorization is implemented in the software package CoGAPS. We describe the application of this software and several technical considerations for identification of age-related patterns in a public, prefrontal cortex gene expression dataset.

Physico-chemical characterization of products from vacuum oil under delayed coking process by infrared spectroscopy and chemometrics methods

NASA Astrophysics Data System (ADS)

Meléndez, L. V.; Cabanzo, R.; Mejía-Ospino, E.; Guzmán, A.

2016-02-01

Eight vacuum residues and their delayed coking liquids products from Colombian crude were study by infrared spectroscopy with attenuated total reflectance (FTIR-ATR) and principal component analysis (PCA). For the samples the structural parameters of aromaticity factor (fa), alifaticity (A2500-3100cm-1), aromatic condensation degree (GCA), length of aliphatic chains (LCA) and aliphatic chain length associated with aromatic (LACAR) were determined through the development of a methodology, which includes the previous processing of spectroscopy data, identifying the regions in the IR spectra of greatest variance using PCA and molecules patterns. The parameters were compared with the results obtained from proton magnetic resonance (1H-NMR) and 13C-NMR. The results showed the influence and correlation of structural parameters with some physicochemical properties such as API gravity, weight percent sulphur (% S) and Conradson carbon content (% CCR)

Structured Sparse Principal Components Analysis With the TV-Elastic Net Penalty.

PubMed

de Pierrefeu, Amicie; Lofstedt, Tommy; Hadj-Selem, Fouad; Dubois, Mathieu; Jardri, Renaud; Fovet, Thomas; Ciuciu, Philippe; Frouin, Vincent; Duchesnay, Edouard

2018-02-01

Principal component analysis (PCA) is an exploratory tool widely used in data analysis to uncover the dominant patterns of variability within a population. Despite its ability to represent a data set in a low-dimensional space, PCA's interpretability remains limited. Indeed, the components produced by PCA are often noisy or exhibit no visually meaningful patterns. Furthermore, the fact that the components are usually non-sparse may also impede interpretation, unless arbitrary thresholding is applied. However, in neuroimaging, it is essential to uncover clinically interpretable phenotypic markers that would account for the main variability in the brain images of a population. Recently, some alternatives to the standard PCA approach, such as sparse PCA (SPCA), have been proposed, their aim being to limit the density of the components. Nonetheless, sparsity alone does not entirely solve the interpretability problem in neuroimaging, since it may yield scattered and unstable components. We hypothesized that the incorporation of prior information regarding the structure of the data may lead to improved relevance and interpretability of brain patterns. We therefore present a simple extension of the popular PCA framework that adds structured sparsity penalties on the loading vectors in order to identify the few stable regions in the brain images that capture most of the variability. Such structured sparsity can be obtained by combining, e.g., and total variation (TV) penalties, where the TV regularization encodes information on the underlying structure of the data. This paper presents the structured SPCA (denoted SPCA-TV) optimization framework and its resolution. We demonstrate SPCA-TV's effectiveness and versatility on three different data sets. It can be applied to any kind of structured data, such as, e.g., -dimensional array images or meshes of cortical surfaces. The gains of SPCA-TV over unstructured approaches (such as SPCA and ElasticNet PCA) or structured approach (such as GraphNet PCA) are significant, since SPCA-TV reveals the variability within a data set in the form of intelligible brain patterns that are easier to interpret and more stable across different samples.

Reading Achievement in Relation to Phonological Coding and Awareness in Deaf Readers: A Meta-Analysis

ERIC Educational Resources Information Center

Mayberry, Rachel I.; del Giudice, Alex A.; Lieberman, Amy M.

2011-01-01

The relation between reading ability and phonological coding and awareness (PCA) skills in individuals who are severely and profoundly deaf was investigated with a meta-analysis. From an initial set of 230 relevant publications, 57 studies were analyzed that experimentally tested PCA skills in 2,078 deaf participants. Half of the studies found…

Dietary intake in midlife and associations with standard of living, education and nutrition literacy.

PubMed

Wall, Catherine L; Gearry, Richard B; Pearson, John; Parnell, Winsome; Skidmore, Paula M L

2014-07-04

Cardiovascular disease is a leading cause of death in New Zealand, but risk factors may be decreased by consuming a heart healthy diet. This pilot study investigated whether participants met the guidelines for a heart healthy diet and whether a novel heart healthy dietary pattern could be identified using principal components analysis (PCA). The second aim of this project was to assess if higher education, standard of living and nutrition literacy are associated with a heart healthy dietary pattern. This exploratory study was undertaken using data from the first participants enrolled in the Canterbury Health Ageing and Lifecourse study: an observational study of 50 year olds in the Canterbury District Health Board region. Eighty-two people were selected from the General and Maori electoral role and interviewed prior to the 22 February 2011 Christchurch Earthquake. PCA was conducted to identify dietary patterns, based on intake of specific nutrients as indicated by the New Zealand and international heart healthy dietary guidelines. 62 participants completed questionnaires and an estimated food record. No participants met all five of the heart healthy dietary guidelines. One dietary pattern was produced by PCA: a "higher CVD risk" pattern. Regression analysis indicated that higher standard of living, education and nutrition literacy were inversely associated with a "higher CVD risk" pattern. Higher standard of living, education and nutrition literacy were associated with a healthier dietary eating pattern. However, as no participants met all the dietary recommendations more education and support is needed to help people meet these.

Temporal and spatial assessment of river surface water quality using multivariate statistical techniques: a study in Can Tho City, a Mekong Delta area, Vietnam.

PubMed

Phung, Dung; Huang, Cunrui; Rutherford, Shannon; Dwirahmadi, Febi; Chu, Cordia; Wang, Xiaoming; Nguyen, Minh; Nguyen, Nga Huy; Do, Cuong Manh; Nguyen, Trung Hieu; Dinh, Tuan Anh Diep

2015-05-01

The present study is an evaluation of temporal/spatial variations of surface water quality using multivariate statistical techniques, comprising cluster analysis (CA), principal component analysis (PCA), factor analysis (FA) and discriminant analysis (DA). Eleven water quality parameters were monitored at 38 different sites in Can Tho City, a Mekong Delta area of Vietnam from 2008 to 2012. Hierarchical cluster analysis grouped the 38 sampling sites into three clusters, representing mixed urban-rural areas, agricultural areas and industrial zone. FA/PCA resulted in three latent factors for the entire research location, three for cluster 1, four for cluster 2, and four for cluster 3 explaining 60, 60.2, 80.9, and 70% of the total variance in the respective water quality. The varifactors from FA indicated that the parameters responsible for water quality variations are related to erosion from disturbed land or inflow of effluent from sewage plants and industry, discharges from wastewater treatment plants and domestic wastewater, agricultural activities and industrial effluents, and contamination by sewage waste with faecal coliform bacteria through sewer and septic systems. Discriminant analysis (DA) revealed that nephelometric turbidity units (NTU), chemical oxygen demand (COD) and NH₃ are the discriminating parameters in space, affording 67% correct assignation in spatial analysis; pH and NO₂ are the discriminating parameters according to season, assigning approximately 60% of cases correctly. The findings suggest a possible revised sampling strategy that can reduce the number of sampling sites and the indicator parameters responsible for large variations in water quality. This study demonstrates the usefulness of multivariate statistical techniques for evaluation of temporal/spatial variations in water quality assessment and management.

Fourier Transform Infrared Spectroscopy (FTIR) and Multivariate Analysis for Identification of Different Vegetable Oils Used in Biodiesel Production

PubMed Central

Mueller, Daniela; Ferrão, Marco Flôres; Marder, Luciano; da Costa, Adilson Ben; de Cássia de Souza Schneider, Rosana

2013-01-01

The main objective of this study was to use infrared spectroscopy to identify vegetable oils used as raw material for biodiesel production and apply multivariate analysis to the data. Six different vegetable oil sources—canola, cotton, corn, palm, sunflower and soybeans—were used to produce biodiesel batches. The spectra were acquired by Fourier transform infrared spectroscopy using a universal attenuated total reflectance sensor (FTIR-UATR). For the multivariate analysis principal component analysis (PCA), hierarchical cluster analysis (HCA), interval principal component analysis (iPCA) and soft independent modeling of class analogy (SIMCA) were used. The results indicate that is possible to develop a methodology to identify vegetable oils used as raw material in the production of biodiesel by FTIR-UATR applying multivariate analysis. It was also observed that the iPCA found the best spectral range for separation of biodiesel batches using FTIR-UATR data, and with this result, the SIMCA method classified 100% of the soybean biodiesel samples. PMID:23539030

A pilot study of prostate cancer knowledge among African American men and their health care advocates: implications for screening decisions.

PubMed

Oliver, JoAnn S; Allen, Rebecca S; Eichorst, Morgan K; Mieskowski, Lisa; Ewell, Patrick J; Payne-Foster, Pamela; Ragin, Camille

2018-05-26

Prostate cancer (PCa) is the second leading cause of cancer death in U.S. men [American Cancer Society (ACS)], most often affecting men age 50 and older. The study provides information about factors that influence rural AA men in their decision to undergo screening for PCa with a specific focus on PCa knowledge among AA men and their health care advocates. A longitudinal quantitative study included AA males and their health care advocates. Participants were from three Alabama rural counties. Measures included demographics, PCa knowledge, decisional conflict, and health literacy scales. Thirty-three men with a mean age of 54.61 and 35 health care advocates were included in the study. PROCASE Knowledge Index measure results indicate a lack of PCa knowledge among both male primary participants and their advocates. The knowledge of AA men in the study was somewhat low, with individuals correctly answering approximately six questions out of ten at multiple time points (baseline total M = 6.42, SD = 1.52). Decisional conflict responses at 12 months (38.64) were lower than at baseline (M = 62.88) and at 6 months (M = 58.33), p < .005. Health care advocates of the 33 male participants were usually women, spouses, or significant others, supporting the vital role women play in men's health specifically in rural underserved communities. Low overall PCa knowledge, including their risk for PCa, among these participants indicates a need for PCa and screening educational interventions and dialogue that include males and their significant others.

Combining chemometric tools for assessing hazard sources and factors acting simultaneously in contaminated areas. Case study: "Mar Piccolo" Taranto (South Italy).

PubMed

Mali, Matilda; Dell'Anna, Maria Michela; Notarnicola, Michele; Damiani, Leonardo; Mastrorilli, Piero

2017-10-01

Almost all marine coastal ecosystems possess complex structural and dynamic characteristics, which are influenced by anthropogenic causes and natural processes as well. Revealing the impact of sources and factors controlling the spatial distributions of contaminants within highly polluted areas is a fundamental propaedeutic step of their quality evaluation. Combination of different pattern recognition techniques, applied to one of the most polluted Mediterranean coastal basin, resulted in a more reliable hazard assessment. PCA/CA and factorial ANOVA were exploited as complementary techniques for apprehending the impact of multi-sources and multi-factors acting simultaneously and leading to similarities or differences in the spatial contamination pattern. The combination of PCA/CA and factorial ANOVA allowed, on one hand to determine the main processes and factors controlling the contamination trend within different layers and different basins, and, on the other hand, to ascertain possible synergistic effects. This approach showed the significance of a spatially representative overview given by the combination of PCA-CA/ANOVA in inferring the historical anthropogenic sources loading on the area. Copyright © 2017 Elsevier Ltd. All rights reserved.

Influence factors and forecast of carbon emission in China: structure adjustment for emission peak

NASA Astrophysics Data System (ADS)

Wang, B.; Cui, C. Q.; Li, Z. P.

2018-02-01

This paper introduced Principal Component Analysis and Multivariate Linear Regression Model to verify long-term balance relationships between Carbon Emissions and the impact factors. The integrated model of improved PCA and multivariate regression analysis model is attainable to figure out the pattern of carbon emission sources. Main empirical results indicate that among all selected variables, the role of energy consumption scale was largest. GDP and Population follow and also have significant impacts on carbon emission. Industrialization rate and fossil fuel proportion, which is the indicator of reflecting the economic structure and energy structure, have a higher importance than the factor of urbanization rate and the dweller consumption level of urban areas. In this way, some suggestions are put forward for government to achieve the peak of carbon emissions.