Metabonomics study of the effects of pretreatment with glycyrrhetinic acid on mesaconitine-induced toxicity in rats.

PubMed

Sun, Bo; Zhang, Ming; Zhang, Qi; Ma, Kunpeng; Li, Haijing; Li, Famei; Dong, Fangting; Yan, Xianzhong

2014-07-03

Aconitum carmichaelii Debx. (Fuzi), a commonly use traditional Chinese medicine (TCM), has often been used in combination with Rhizoma Glycyrrhizae (Gancao) to reduce its toxicity due to diester diterpenoid alkaloids aconitine, mesaconitine, and hypaconitine. However, the mechanism of detoxication is still unclear. Glycyrrhetinic acid (GA) is the metabolite of glycyrrhizinic acid (GL), the major component of Gancao. In present study, the effect of GA on the changes of metabolic profiles induced by mesaconitine was investigated using NMR-based metabolomic approaches. Fifteen male Wistar rats were divided into a control group, a group administered mesaconitine alone, and a group administered mesaconitine with one pretreatment with GA. Their urine samples were used for NMR spectroscopic metabolic profiling. Statistical analyses such as orthogonal projections to latent structures-discriminant analysis (OPLS-DA), t-test, hierarchical cluster, and pathway analysis were used to detect the effects of pretreatment with GA on mesaconitine-induced toxicity. The OPLS-DA score plots showed the metabolic profiles of GA-pretreated rats apparently approach to those of normal rats compared to mesaconitine-induced rats. From the t-test and boxplot results, the concentrations of leucine/isoleucine, lactate, acetate, succinate, trimethylamine (TMA), dimethylglycine (DMG), 2-oxo-glutarate, creatinine/creatine, glycine, hippurate, tyrosine and benzoate were significantly changed in metabolic profiles of mesaconitine-induced rats. The disturbed metabolic pathways include amino acid biosynthesis and metabolism. GA-pretreatment can mitigate the metabolic changes caused by mesaconitine-treatment on rats, indicating that prophylaxis with GA could reduce the toxicity of mesaconitine at the metabolic level. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Quantification of coffee blends for authentication of Asian palm civet coffee (Kopi Luwak) via metabolomics: A proof of concept.

PubMed

Jumhawan, Udi; Putri, Sastia Prama; Yusianto; Bamba, Takeshi; Fukusaki, Eiichiro

2016-07-01

Asian palm civet coffee (Kopi Luwak), an animal-digested coffee with an exotic feature, carries a notorious reputation of being the rarest and most expensive coffee beverage in the world. Considering that illegal mixture of cheap coffee into civet coffee is a growing concern among consumers, we evaluated the use of metabolomics approach and orthogonal projection to latent structures (OPLS) prediction technique to quantify the degree of coffee adulteration. Two prediction sets, consisting of certified and commercial coffee, were made from a blend of civet and regular coffee with eleven mixing percentages. The prediction model exhibited accurate estimation of coffee blend percentage thus, successfully validating the prediction and quantification of the mixing composition of known-unknown samples. This work highlighted proof of concept of metabolomics application to predict degree of coffee adulteration by determining the civet coffee fraction in blends. Copyright © 2016 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.

The adjuvanticity of ophiopogon polysaccharide liposome against an inactivated porcine parvovirus vaccine in mice.

PubMed

Fan, Yunpeng; Ma, Xia; Hou, Weifeng; Guo, Chao; Zhang, Jing; Zhang, Weimin; Ma, Lin; Song, Xiaoping

2016-01-01

In this study, the adjuvant activity of ophiopogon polysaccharide liposome (OPL) was investigated. The effects of OPL on the splenic lymphocyte proliferation of mice were measured in vitro. The results showed that OPL could significantly promote lymphocyte proliferation singly or synergistically with PHA and LPS and that the effect was better than ophiopogon polysaccharide (OP) at most of concentrations. The adjuvant activities of OPL, OP and mineral oil were compared in BALB/c mice inoculated with inactivated PPV in vivo. The results showed that OPL could significantly enhance lymphocyte proliferation, increase the proportion of CD4(+) and CD8(+) T cells, improve the HI antibody titre and specific IgG response, and promote the production of cytokines, and the efficacy of OPL was significantly better than that of OP. In addition, OPL significantly improved the cellular immune response compared with oil adjuvant. These results suggested that OPL possess superior adjuvanticity and that a medium dose had the best efficacy. Therefore, OPL can be used as an effective immune adjuvant for an inactivated PPV vaccine. Copyright © 2015. Published by Elsevier B.V.

Different foveal schisis patterns in each retinal layer in eyes with hereditary juvenile retinoschisis evaluated by en-face optical coherence tomography.

PubMed

Yoshida-Uemura, Tomoyo; Katagiri, Satoshi; Yokoi, Tadashi; Nishina, Sachiko; Azuma, Noriyuki

2017-04-01

To analyze the structures of schisis in eyes with hereditary juvenile retinoschisis using en-face optical coherence tomography (OCT) imaging. In this retrospective observational study, we reviewed the medical records of patients with hereditary juvenile retinoschisis who underwent comprehensive ophthalmic examinations including swept-source OCT. OCT images were obtained from 16 eyes of nine boys (mean age ± standard deviation, 10.6 ± 4.0 years). The horizontal OCT images at the fovea showed inner nuclear layer (INL) schisis in one eye (6.3 %), ganglion cell layer (GCL) and INL schisis in 12 eyes (75.0 %), INL and outer plexiform layer (OPL) schisis in two eyes (12.5 %), and GCL, INL, and OPL schisis in one eye (6.3 %). En-face OCT images showed characteristic schisis patterns in each retinal layer, which were represented by multiple hyporeflective holes in the parafoveal region in the GCL, a spoke-like pattern in the foveal region, a reticular pattern in the parafoveal region in the INL, and multiple hyporeflective polygonal cavities with partitions in the OPL. Our results using en-face OCT imaging clarified different patterns of schisis formation among the GCL, INL, and OPL, which lead to further recognition of structure in hereditary juvenile retinoschisis.

Metabonomics study of the therapeutic mechanism of fenugreek galactomannan on diabetic hyperglycemia in rats, by ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry.

PubMed

Jiang, Wenyue; Gao, Lu; Li, Pengdong; Kan, Hong; Qu, Jiale; Men, Lihui; Liu, Zhiqiang; Liu, Zhongying

2017-02-15

Fenugreek is a traditional plant for the treatment of diabetes. Galactomannan, an active major component in fenugreek seeds, has shown hypoglycemic activity. The present study was performed to investigate the therapeutic mechanism underlying fenugreek galactomannan (F-GAL) in treating diabetes, using a metabonomics approach based on ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC-QTOF/MS). The F-GAL used for study was highly purified, and its yield, purity, and galactose/mannose ratio were characterized by capillary zone electrophoresis (CZE) and a modified phenol-sulfuric acid method. After treatment of streptozotocin (STZ)-induced diabetic rats with F-GAL for 28days, urine and serum samples were analyzed by UPLC-QTOF/MS. Multivariate statistical approaches such as principal component analysis (PCA) and orthogonal projection to latent structures squares-discriminant analysis (OPLS-DA) were applied to distinguish the non-diabetic/untreated, diabetic/untreated, and diabetic/F-GAL-treated groups. Then, potential biomarkers were identified that may help elucidate the underlying therapeutic mechanism of F-GAL in diabetes. The results demonstrated that there was a clear separation among the three groups in the PCA model. Fourteen potential biomarkers were identified by OPLS-DA, and they were determined to be produced in response to the therapeutic effects of F-GAL. These biomarkers were involved in histidine metabolism, tryptophan metabolism, energy metabolism, phenylalanine metabolism, sphingolipid metabolism, glycerophospholipid metabolism, and arachidonic acid metabolism. In conclusion, our study demonstrates that a metabonomics approach is a powerful, novel tool that can be used to evaluate the underlying therapeutic mechanisms of herb extracts. Copyright © 2016 Elsevier B.V. All rights reserved.

HR-MAS MR Spectroscopy of Breast Cancer Tissue Obtained with Core Needle Biopsy: Correlation with Prognostic Factors

PubMed Central

Choi, Ji Soo; Baek, Hyeon-Man; Kim, Suhkmann; Kim, Min Jung; Youk, Ji Hyun; Moon, Hee Jung; Kim, Eun-Kyung; Han, Kyung Hwa; Kim, Dong-hyun; Kim, Seung Il; Koo, Ja Seung

2012-01-01

The purpose of this study was to examine the correlation between high-resolution magic angle spinning (HR-MAS) magnetic resonance (MR) spectroscopy using core needle biopsy (CNB) specimens and histologic prognostic factors currently used in breast cancer patients. After institutional review board approval and informed consent were obtained for this study, CNB specimens were collected from 36 malignant lesions in 34 patients. Concentrations and metabolic ratios of various choline metabolites were estimated by HR-MAS MR spectroscopy using CNB specimens. HR-MAS spectroscopic values were compared according to histopathologic variables [tumor size, lymph node metastasis, histologic grade, status of estrogens receptor (ER), progesterone receptor (PR), HER2 (a receptor for human epidermal growth factor), and Ki-67, and triple negativity]. Multivariate analysis was performed with Orthogonal Projections to Latent Structure-Discriminant Analysis (OPLS-DA). HR-MAS MR spectroscopy quantified and discriminated choline metabolites in all CNB specimens of the 36 breast cancers. Several metabolite markers [free choline (Cho), phosphocholine (PC), creatine (Cr), taurine, myo-inositol, scyllo-inositol, total choline (tCho), glycine, Cho/Cr, tCho/Cr, PC/Cr] on HR-MAS MR spectroscopy were found to correlate with histologic prognostic factors [ER, PR, HER2, histologic grade, triple negativity, Ki-67, poor prognosis]. OPLS-DA multivariate models were generally able to discriminate the status of histologic prognostic factors (ER, PR, HER2, Ki-67) and prognosis groups. Our study suggests that HR-MAS MR spectroscopy using CNB specimens can predict tumor aggressiveness prior to surgery in breast cancer patients. In addition, it may be helpful in the detection of reliable markers for breast cancer characterization. PMID:23272149

Magnetic resonance metabolic profiling of estrogen receptor-positive breast cancer: correlation with currently used molecular markers

PubMed Central

Koo, Ja Seung; Kim, Siwon; Park, Vivian Youngjean; Kim, Eun-Kyung; Kim, Suhkmann; Kim, Min Jung

2017-01-01

Estrogen receptor (ER)-positive breast cancers overall have a good prognosis, however, some patients suffer relapses and do not respond to endocrine therapy. The purpose of this study was to determine whether there are any correlations between high-resolution magic angle spinning (HR-MAS) magnetic resonance spectroscopy (MRS) metabolic profiles of core needle biopsy (CNB) specimens and the molecular markers currently used in patients with ER-positive breast cancers. The metabolic profiling of CNB samples from 62 ER-positive cancers was performed by HR-MAS MRS. Metabolic profiles were compared according to human epidermal growth factor receptor 2 (HER2) and Ki-67 status, and luminal type, using the Mann-Whitney test. Multivariate analysis was performed with orthogonal projections to latent structure-discriminant analysis (OPLS-DA). In univariate analysis, the HER2-positive group was shown to have higher levels of glycine and glutamate, compared to the HER2-negative group (P<0.01, and P <0.01, respectively). The high Ki-67 group showed higher levels of glutamate than the low Ki-67 group without statistical significance. Luminal B cancers showed higher levels of glycine (P=0.01) than luminal A cancers. In multivariate analysis, the OPLS-DA models built with HR-MAS MR metabolic profiles showed visible discrimination between the subgroups according to HER2 and Ki-67 status, and luminal type. This study showed that the metabolic profiles of CNB samples assessed by HR-MAS MRS can be used to detect potential prognostic biomarkers as well as to understand the difference in metabolic mechanism among subtypes of ER-positive breast cancer. PMID:28969000

Protein biomarkers in vernix with potential to predict the development of atopic eczema in early childhood

PubMed Central

Holm, T; Rutishauser, D; Kai-Larsen, Y; Lyutvinskiy, Y; Stenius, F; Zubarev, R A; Agerberth, B; Alm, J; Scheynius, A

2014-01-01

Background Atopic eczema (AE) is a chronic inflammatory skin disease, which has increased in prevalence. Evidence points toward lifestyle as a major risk factor. AE is often the first symptom early in life later followed by food allergy, asthma, and allergic rhinitis. Thus, there is a great need to find early, preferentially noninvasive, biomarkers to identify individuals that are predisposed to AE with the goal to prevent disease development. Objective To investigate whether the protein abundances in vernix can predict later development of AE. Methods Vernix collected at birth from 34 newborns within the Assessment of Lifestyle and Allergic Disease During INfancy (ALADDIN) birth cohort was included in the study. At 2 years of age, 18 children had developed AE. Vernix proteins were identified and quantified with liquid chromatography coupled to tandem mass spectrometry. Results We identified and quantified 203 proteins in all vernix samples. An orthogonal projections to latent structures-discriminant analysis (OPLS-DA) model was found with R2 = 0.85, Q2 = 0.39, and discrimination power between the AE and healthy group of 73.5%. Polyubiquitin-C and calmodulin-like protein 5 showed strong negative correlation to the AE group, with a correlation coefficient of 0.73 and 0.68, respectively, and a P-value of 8.2 E-7 and 1.8 E-5, respectively. For these two proteins, the OPLS-DA model showed a prediction accuracy of 91.2%. Conclusion The protein abundances in vernix, and particularly that of polyubiquitin-C and calmodulin-like protein 5, are promising candidates as biomarkers for the identification of newborns predisposed to develop AE. PMID:24205894

A Comprehensive Evaluation of Steroid Metabolism in Women with Intrahepatic Cholestasis of Pregnancy

PubMed Central

Pařízek, Antonín; Hill, Martin; Dušková, Michaela; Vítek, Libor; Velíková, Marta; Kancheva, Radmila; Šimják, Patrik; Koucký, Michal; Kokrdová, Zuzana; Adamcová, Karolína; Černý, Andrej; Hájek, Zdeněk; Stárka, Luboslav

2016-01-01

Intrahepatic cholestasis of pregnancy (ICP) is a common liver disorder, mostly occurring in the third trimester. ICP is defined as an elevation of serum bile acids, typically accompanied by pruritus and elevated activities of liver aminotransferases. ICP is caused by impaired biliary lipid secretion, in which endogenous steroids may play a key role. Although ICP is benign for the pregnant woman, it may be harmful for the fetus. We evaluated the differences between maternal circulating steroids measured by RIA (17-hydroxypregnenolone and its sulfate, 17-hydroxyprogesterone, and cortisol) and GC-MS (additional steroids), hepatic aminotransferases and bilirubin in women with ICP (n = 15, total bile acids (TBA) >8 μM) and corresponding controls (n = 17). An age-adjusted linear model, receiver-operating characteristics (ROC), and multivariate regression (a method of orthogonal projections to latent structure, OPLS) were used for data evaluation. While aminotransferases, conjugates of pregnanediols, 17-hydroxypregnenolone and 5β-androstane-3α,17β-diol were higher in ICP patients, 20α-dihydropregnenolone, 16α-hydroxy-steroids, sulfated 17-oxo-C19-steroids, and 5β-reduced steroids were lower. The OPLS model including steroids measured by GC-MS and RIA showed 93.3% sensitivity and 100% specificity, while the model including steroids measured by GC-MS in a single sample aliquot showed 93.3% sensitivity and 94.1% specificity. A composite index including ratios of sulfated 3α/β-hydroxy-5α/β-androstane-17-ones to conjugated 5α/β-pregnane-3α/β, 20α-diols discriminated with 93.3% specificity and 81.3% sensitivity (ROC analysis). These new data demonstrating altered steroidogenesis in ICP patients offer more detailed pathophysiological insights into the role of steroids in the development of ICP. PMID:27494119

Characteristic glycopeptides associated with extreme human longevity identified through plasma glycoproteomics.

PubMed

Miura, Yuri; Hashii, Noritaka; Ohta, Yuki; Itakura, Yoko; Tsumoto, Hiroki; Suzuki, Junya; Takakura, Daisuke; Abe, Yukiko; Arai, Yasumichi; Toyoda, Masashi; Kawasaki, Nana; Hirose, Nobuyoshi; Endo, Tamao

2018-06-01

Glycosylation is highly susceptible to changes of the physiological conditions, and accordingly, is a potential biomarker associated with several diseases and/or longevity. Semi-supercentenarians (SSCs; older than 105 years) are thought to be a model of human longevity. Thus, we performed glycoproteomics using plasma samples of SSCs, and identified proteins and conjugated N-glycans that are characteristic of extreme human longevity. Plasma proteins from Japanese semi-supercentenarians (SSCs, 106-109 years), aged controls (70-88 years), and young controls (20-38 years) were analysed by using lectin microarrays and liquid chromatography/mass spectrometry (LC/MS). Peak area ratios of glycopeptides to corresponding normalising peptides were subjected to orthogonal projections to latent structures discriminant analysis (OPLS-DA). Furthermore, plasma levels of clinical biomarkers were measured. We found two lectins such as Phaseolus vulgaris, and Erythrina cristagalli (ECA), of which protein binding were characteristically increased in SSCs. Peak area ratios of ECA-enriched glycopeptides were successfully discriminated between SSCs and controls using OPLS-DA, and indicated that tri-antennary and sialylated N-glycans of haptoglobin at Asn207 and Asn211 sites were characterized in SSCs. Sialylated glycans of haptoglobin are a potential biomarker of several diseases, such as hepatocellular carcinoma, liver cirrhosis, and IgA-nephritis. However, the SSCs analysed here did not suffer from these diseases. Tri-antennary and sialylated N-glycans on haptoglobin at the Asn207 and Asn211 sites were abundant in SSCs and characteristic of extreme human longevity. We found abundant glycans in SSCs, which may be associated with human longevity. Copyright © 2018 Elsevier B.V. All rights reserved.

Statistical process control of cocrystallization processes: A comparison between OPLS and PLS.

PubMed

Silva, Ana F T; Sarraguça, Mafalda Cruz; Ribeiro, Paulo R; Santos, Adenilson O; De Beer, Thomas; Lopes, João Almeida

2017-03-30

Orthogonal partial least squares regression (OPLS) is being increasingly adopted as an alternative to partial least squares (PLS) regression due to the better generalization that can be achieved. Particularly in multivariate batch statistical process control (BSPC), the use of OPLS for estimating nominal trajectories is advantageous. In OPLS, the nominal process trajectories are expected to be captured in a single predictive principal component while uncorrelated variations are filtered out to orthogonal principal components. In theory, OPLS will yield a better estimation of the Hotelling's T 2 statistic and corresponding control limits thus lowering the number of false positives and false negatives when assessing the process disturbances. Although OPLS advantages have been demonstrated in the context of regression, its use on BSPC was seldom reported. This study proposes an OPLS-based approach for BSPC of a cocrystallization process between hydrochlorothiazide and p-aminobenzoic acid monitored on-line with near infrared spectroscopy and compares the fault detection performance with the same approach based on PLS. A series of cocrystallization batches with imposed disturbances were used to test the ability to detect abnormal situations by OPLS and PLS-based BSPC methods. Results demonstrated that OPLS was generally superior in terms of sensibility and specificity in most situations. In some abnormal batches, it was found that the imposed disturbances were only detected with OPLS. Copyright © 2017 Elsevier B.V. All rights reserved.

Metabolomic Analysis in Severe Childhood Pneumonia in The Gambia, West Africa: Findings from a Pilot Study

PubMed Central

Laiakis, Evagelia C.; Morris, Gerard A. J.; Fornace, Albert J.; Howie, Stephen R. C.

2010-01-01

Background Pneumonia remains the leading cause of death in young children globally and improved diagnostics are needed to better identify cases and reduce case fatality. Metabolomics, a rapidly evolving field aimed at characterizing metabolites in biofluids, has the potential to improve diagnostics in a range of diseases. The objective of this pilot study is to apply metabolomic analysis to childhood pneumonia to explore its potential to improve pneumonia diagnosis in a high-burden setting. Methodology/Principal Findings Eleven children with World Health Organization (WHO)-defined severe pneumonia of non-homogeneous aetiology were selected in The Gambia, West Africa, along with community controls. Metabolomic analysis of matched plasma and urine samples was undertaken using Ultra Performance Liquid Chromatography (UPLC) coupled to Time-of-Flight Mass Spectrometry (TOFMS). Biomarker extraction was done using SIMCA-P+ and Random Forests (RF). ‘Unsupervised’ (blinded) data were analyzed by Principal Component Analysis (PCA), while ‘supervised’ (unblinded) analysis was by Partial Least Squares-Discriminant Analysis (PLS-DA) and Orthogonal Projection to Latent Structures (OPLS). Potential markers were extracted from S-plots constructed following analysis with OPLS, and markers were chosen based on their contribution to the variation and correlation within the data set. The dataset was additionally analyzed with the machine-learning algorithm RF in order to address issues of model overfitting and markers were selected based on their variable importance ranking. Unsupervised PCA analysis revealed good separation of pneumonia and control groups, with even clearer separation of the groups with PLS-DA and OPLS analysis. Statistically significant differences (p<0.05) between groups were seen with the following metabolites: uric acid, hypoxanthine and glutamic acid were higher in plasma from cases, while L-tryptophan and adenosine-5′-diphosphate (ADP) were lower; uric acid and L-histidine were lower in urine from cases. The key limitation of this study is its small size. Conclusions/Significance Metabolomic analysis clearly distinguished severe pneumonia patients from community controls. The metabolites identified are important for the host response to infection through antioxidant, inflammatory and antimicrobial pathways, and energy metabolism. Larger studies are needed to determine whether these findings are pneumonia-specific and to distinguish organism-specific responses. Metabolomics has considerable potential to improve diagnostics for childhood pneumonia. PMID:20844590

Metabolomic analysis in severe childhood pneumonia in the Gambia, West Africa: findings from a pilot study.

PubMed

Laiakis, Evagelia C; Morris, Gerard A J; Fornace, Albert J; Howie, Stephen R C

2010-09-09

Pneumonia remains the leading cause of death in young children globally and improved diagnostics are needed to better identify cases and reduce case fatality. Metabolomics, a rapidly evolving field aimed at characterizing metabolites in biofluids, has the potential to improve diagnostics in a range of diseases. The objective of this pilot study is to apply metabolomic analysis to childhood pneumonia to explore its potential to improve pneumonia diagnosis in a high-burden setting. Eleven children with World Health Organization (WHO)-defined severe pneumonia of non-homogeneous aetiology were selected in The Gambia, West Africa, along with community controls. Metabolomic analysis of matched plasma and urine samples was undertaken using Ultra Performance Liquid Chromatography (UPLC) coupled to Time-of-Flight Mass Spectrometry (TOFMS). Biomarker extraction was done using SIMCA-P+ and Random Forests (RF). 'Unsupervised' (blinded) data were analyzed by Principal Component Analysis (PCA), while 'supervised' (unblinded) analysis was by Partial Least Squares-Discriminant Analysis (PLS-DA) and Orthogonal Projection to Latent Structures (OPLS). Potential markers were extracted from S-plots constructed following analysis with OPLS, and markers were chosen based on their contribution to the variation and correlation within the data set. The dataset was additionally analyzed with the machine-learning algorithm RF in order to address issues of model overfitting and markers were selected based on their variable importance ranking. Unsupervised PCA analysis revealed good separation of pneumonia and control groups, with even clearer separation of the groups with PLS-DA and OPLS analysis. Statistically significant differences (p<0.05) between groups were seen with the following metabolites: uric acid, hypoxanthine and glutamic acid were higher in plasma from cases, while L-tryptophan and adenosine-5'-diphosphate (ADP) were lower; uric acid and L-histidine were lower in urine from cases. The key limitation of this study is its small size. Metabolomic analysis clearly distinguished severe pneumonia patients from community controls. The metabolites identified are important for the host response to infection through antioxidant, inflammatory and antimicrobial pathways, and energy metabolism. Larger studies are needed to determine whether these findings are pneumonia-specific and to distinguish organism-specific responses. Metabolomics has considerable potential to improve diagnostics for childhood pneumonia.

A mitochondria-dependent pathway mediates the apoptosis of GSE-induced yeast.

PubMed

Cao, Sishuo; Xu, Wentao; Zhang, Nan; Wang, Yan; Luo, YunBo; He, Xiaoyun; Huang, Kunlun

2012-01-01

Grapefruit seed extract (GSE), which has powerful anti-fungal activity, can induce apoptosis in S. cerevisiae. The yeast cells underwent apoptosis as determined by testing for apoptotic markers of DNA cleavage and typical chromatin condensation by Terminal Deoxynucleotidyl Transferase-mediated dUTP Nick End Labeling (TUNEL) and 4,6'-diaminidino-2-phenylindole (DAPI) staining and electron microscopy. The changes of ΔΨmt (mitochondrial transmembrane potential) and ROS (reactive oxygen species) indicated that the mitochondria took part in the apoptotic process. Changes in this process detected by metabonomics and proteomics revealed that the yeast cells tenaciously resisted adversity. Proteins related to redox, cellular structure, membrane, energy and DNA repair were significantly increased. In this study, the relative changes in the levels of proteins and metabolites showed the tenacious resistance of yeast cells. However, GSE induced apoptosis in the yeast cells by destruction of the mitochondrial 60 S ribosomal protein, L14-A, and prevented the conversion of pantothenic acid to coenzyme A (CoA). The relationship between the proteins and metabolites was analyzed by orthogonal projections to latent structures (OPLS). We found that the changes of the metabolites and the protein changes had relevant consistency.

A Mitochondria-Dependent Pathway Mediates the Apoptosis of GSE-Induced Yeast

PubMed Central

Cao, Sishuo; Xu, Wentao; Zhang, Nan; Wang, Yan; Luo, YunBo; He, Xiaoyun; Huang, Kunlun

2012-01-01

Grapefruit seed extract (GSE), which has powerful anti-fungal activity, can induce apoptosis in S. cerevisiae. The yeast cells underwent apoptosis as determined by testing for apoptotic markers of DNA cleavage and typical chromatin condensation by Terminal Deoxynucleotidyl Transferase–mediated dUTP Nick End Labeling (TUNEL) and 4,6′-diaminidino-2-phenylindole (DAPI) staining and electron microscopy. The changes of ΔΨmt (mitochondrial transmembrane potential) and ROS (reactive oxygen species) indicated that the mitochondria took part in the apoptotic process. Changes in this process detected by metabonomics and proteomics revealed that the yeast cells tenaciously resisted adversity. Proteins related to redox, cellular structure, membrane, energy and DNA repair were significantly increased. In this study, the relative changes in the levels of proteins and metabolites showed the tenacious resistance of yeast cells. However, GSE induced apoptosis in the yeast cells by destruction of the mitochondrial 60 S ribosomal protein, L14-A, and prevented the conversion of pantothenic acid to coenzyme A (CoA). The relationship between the proteins and metabolites was analyzed by orthogonal projections to latent structures (OPLS). We found that the changes of the metabolites and the protein changes had relevant consistency. PMID:22403727

Comparison of the meat metabolite composition of Linwu and Pekin ducks using 600 MHz 1H nuclear magnetic resonance spectroscopy.

PubMed

Wang, Xiangrong; Fang, Chengkun; He, Jianhua; Dai, Qiuzhong; Fang, Rejun

2017-01-01

In an effort to further understand of the differences of meat flavor and texture between Linwu ducks and Pekin ducks at market age, we investigated the meat metabolite composition of the two breeds of ducks using 600 MHz 1 H nuclear magnetic resonance (NMR) spectroscopy. Comprehensive multivariate data analysis including principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), and orthogonal projection to latent structure-discriminant analysis (OPLS-DA) were applied to analyze the 1 H-NMR profiling data to identify the distinguishing metabolites of breast meat between two breeds of ducks. Compared with 42-d-old Pekin duck meat, breast from 72-d-old Linwu duck has higher concentration of anserine, carnosine, homocarnosine, and nicotinamide, but significantly lower concentration of succinate, creatine, and myo-inositol. These results contribute to a better understanding of the differences in meat metabolite composition between 72-d-old Linwu and 42-d-old Pekin ducks, which could be used to help assess the quality of duck meat as a food. © 2016 Poultry Science Association Inc.

Comparative analysis of Hibiscus sabdariffa (roselle) hot and cold extracts in respect to their potential for α-glucosidase inhibition.

PubMed

Rasheed, Dalia M; Porzel, Andrea; Frolov, Andrei; El Seedi, Hesham R; Wessjohann, Ludger A; Farag, Mohamed A

2018-06-01

Roselle (Hibiscus sabdariffa) is a functional food with potential health benefits, consumed either as hot or cold beverage. To ensure quality control of its various products, accurate measurement of active metabolites is warranted. Herein, we propose a combination of ultra-high performance liquid chromatography-mass spectrometry (UHPLC-MS) and nuclear magnetic resonance (NMR) analytical platforms for the untargeted characterization of metabolites in two roselle cultivars, Aswan and Sudan-1. The analyses revealed 33 metabolites, including sugars, flavonoids, anthocyanins, phenolic and aliphatic organic acids. Their relative contents in cultivars were assessed via principle component analysis (PCA) and orthogonal projection to latent structures analysis (OPLS). Impact of the different extraction methods (decoction, infusion and maceration) was compared by quantitative 1 H NMR spectroscopy, revealing cold maceration to be optimal for preserving anthocyanins, whereas infusion was more suited for recovering organic acids. The metabolite pattern revealed by the different extraction methods was found in good correlation for their ability to inhibit α-glucosidase enzyme. Copyright © 2018 Elsevier Ltd. All rights reserved.

Metabolomic profiling of doxycycline treatment in chronic obstructive pulmonary disease.

PubMed

Singh, Brajesh; Jana, Saikat K; Ghosh, Nilanjana; Das, Soumen K; Joshi, Mamata; Bhattacharyya, Parthasarathi; Chaudhury, Koel

2017-01-05

Serum metabolic profiling can identify the metabolites responsible for discrimination between doxycycline treated and untreated chronic obstructive pulmonary disease (COPD) and explain the possible effect of doxycycline in improving the disease conditions. 1 H nuclear magnetic resonance (NMR)-based metabolomics was used to obtain serum metabolic profiles of 60 add-on doxycycline treated COPD patients and 40 patients receiving standard therapy. The acquired data were analyzed using multivariate principal component analysis (PCA), partial least-squares-discriminant analysis (PLS-DA), and orthogonal projection to latent structure with discriminant analysis (OPLS-DA). A clear metabolic differentiation was apparent between the pre and post doxycycline treated group. The distinguishing metabolites lactate and fatty acids were significantly down-regulated and formate, citrate, imidazole and l-arginine upregulated. Lactate and folate are further validated biochemically. Metabolic changes, such as decreased lactate level, inhibited arginase activity and lowered fatty acid level observed in COPD patients in response to add-on doxycycline treatment, reflect the anti-inflammatory action of the drug. Doxycycline as a possible therapeutic option for COPD seems promising. Copyright © 2016 Elsevier B.V. All rights reserved.

Accumulation of Carotenoids and Metabolic Profiling in Different Cultivars of Tagetes Flowers.

PubMed

Park, Yun Ji; Park, Soo-Yun; Valan Arasu, Mariadhas; Al-Dhabi, Naif Abdullah; Ahn, Hyung-Geun; Kim, Jae Kwang; Park, Sang Un

2017-02-18

Species of Tagetes , which belong to the family Asteraceae show different characteristics including, bloom size, shape, and color; plant size; and leaf shape. In this study, we determined the differences in primary metabolites and carotenoid yields among six cultivars from two Tagetes species, T. erecta and T. patula . In total, we detected seven carotenoids in the examined cultivars: violaxanthin, lutein, zeaxanthin, α-carotene, β-carotene, 9- cis -β-carotene, and 13- cis -β-carotene. In all the cultivars, lutein was the most abundant carotenoid. Furthermore, the contents of each carotenoid in flowers varied depending on the cultivar. Principal component analysis (PCA) facilitated metabolic discrimination between Tagetes cultivars, with the exception of Inca Yellow and Discovery Orange. Moreover, PCA and orthogonal projection to latent structure-discriminant analysis (OPLS-DA) results provided a clear discrimination between T. erecta and T. patula . Primary metabolites, including xylose, citric acid, valine, glycine, and galactose were the main components facilitating separation of the species. Positive relationships were apparent between carbon-rich metabolites, including those of the TCA cycle and sugar metabolism, and carotenoids.

Characterization of oils and fats by 1H NMR and GC/MS fingerprinting: classification, prediction and detection of adulteration.

PubMed

Fang, Guihua; Goh, Jing Yeen; Tay, Manjun; Lau, Hiu Fung; Li, Sam Fong Yau

2013-06-01

The correct identification of oils and fats is important to consumers from both commercial and health perspectives. Proton nuclear magnetic resonance ((1)H NMR) spectroscopy, gas chromatography-mass spectrometry (GC/MS) fingerprinting and chemometrics were employed successfully for the quality control of oils and fats. Principal component analysis (PCA) of both techniques showed group clustering of 14 types of oils and fats. Partial least squares discriminant analysis (PLS-DA) and orthogonal projections to latent structures discriminant analysis (OPLS-DA) using GC/MS data had excellent classification sensitivity and specificity compared to models using NMR data. Depending on the availability of the instruments, data from either technique can effectively be applied for the establishment of an oils and fats database to identify unknown samples. Partial least squares (PLS) models were successfully established for the detection of as low as 5% of lard and beef tallow spiked into canola oil, thus illustrating possible applications in Islamic and Jewish countries. Copyright © 2012 Elsevier Ltd. All rights reserved.

OCTOPUS-LIKE 2, a novel player in Arabidopsis root and vascular development, reveals a key role for OCTOPUS family genes in root metaphloem sieve tube differentiation.

PubMed

Ruiz Sola, M Aguila; Coiro, Mario; Crivelli, Simona; Zeeman, Samuel C; Schmidt Kjølner Hansen, Signe; Truernit, Elisabeth

2017-12-01

Protophloem and metaphloem sieve tubes are essential for transporting carbohydrates and signalling molecules towards sink tissues. OCTOPUS (OPS) was previously identified as an important regulator of protophloem differentiation in Arabidopsis roots. Here, we investigated the role of OCTOPUS-LIKE 2 (OPL2), a gene homologous to OPS. OPL2 expression patterns were analysed, and functional equivalence of OPS and OPL2 was tested. Mutant and double mutant phenotypes were investigated. OPS and OPL2 displayed overlapping expression patterns and a high degree of functional overlap. A mutation in OPL2 revealed redundant functions of OPS and OPL2 in developmental processes in which OPS was known to play a role, notably cotyledon vascular patterning and protophloem development. Moreover, we also uncovered redundant roles for OPS and OPL2 in leaf vascular patterning and, most interestingly, metaphloem sieve tube differentiation. Our results reveal a novel OPS-like protein that, together with OPS, is an important regulator of vascular patterning, root growth and phloem development. OPS and OPL2 are the first genes identified that play a role in metaphloem sieve tube differentiation. © 2017 The Authors. New Phytologist © 2017 New Phytologist Trust.

Effect of Varying the 1-4 Intramolecular Scaling Factor in Atomistic Simulations of Long-Chain N-alkanes with the OPLS-AA Model

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

de Almeida, Valmor F; Ye, Xianggui; Cui, Shengting

2013-01-01

A comprehensive molecular dynamics simulation study of n-alkanes using the Optimized Potential for Liquid Simulation-All Atoms (OPLS-AA) force field at ambient condition has been performed. Our results indicate that while simulations with the OPLS-AA force field accurately predict the liquid state mass density for n-alkanes with carbon number equal or less than 10, for n-alkanes with carbon number equal or exceeding 12, the OPLS-AA force field with the standard scaling factor for the 1-4 intramolecular Van der Waals and electrostatic interaction gives rise to a quasi-crystalline structure. We found that accurate predictions of the liquid state properties are obtained bymore » successively reducing the aforementioned scaling factor for each increase of the carbon number beyond n-dodecane. To better un-derstand the effects of reducing the scaling factor, we analyzed the variation of the torsion potential pro-file with the scaling factor, and the corresponding impact on the gauche-trans conformer distribution, heat of vaporization, melting point, and self-diffusion coefficient for n-dodecane. This relatively simple procedure thus allows for more accurate predictions of the thermo-physical properties of longer n-alkanes.« less

Oral precancerous lesions: Problems of early detection and oral cancer prevention

NASA Astrophysics Data System (ADS)

Gileva, Olga S.; Libik, Tatiana V.; Danilov, Konstantin V.

2016-08-01

The study presents the results of the research in the structure, local and systemic risk factors, peculiarities of the clinical manifestation, and quality of primary diagnosis of precancerous oral mucosa lesions (OMLs). In the study a wide range of OMLs and high (25.4%) proportion of oral precancerous lesions (OPLs) in their structure was indicated. The high percentage of different diagnostic errors and the lack of oncological awareness of dental practitioners, as well as the sharp necessity of inclusion of precancer/cancer early detection techniques into their daily practice were noted. The effectiveness of chemilumenescence system of early OPLs and oral cancer detection was demonstrated, the prospects of infrared thermography as a diagnostic tool were also discussed.

Development Approach of the Advanced Life Support On-line Project Information System

NASA Technical Reports Server (NTRS)

Levri, Julie A.; Hogan, John A.; Morrow, Rich; Ho, Michael C.; Kaehms, Bob; Cavazzoni, Jim; Brodbeck, Christina A.; Whitaker, Dawn R.

2005-01-01

The Advanced Life Support (ALS) Program has recently accelerated an effort to develop an On-line Project Information System (OPIS) for research project and technology development data centralization and sharing. There has been significant advancement in the On-line Project Information System (OPIS) over the past year (Hogan et al, 2004). This paper presents the resultant OPIS development approach. OPIS is being built as an application framework consisting of an uderlying Linux/Apache/MySQL/PHP (LAMP) stack, and supporting class libraries that provides database abstraction and automatic code generation, simplifying the ongoing development and maintenance process. Such a development approach allows for quick adaptation to serve multiple Programs, although initial deployment is for an ALS module. OPIS core functionality will involve a Web-based annual solicitation of project and technology data directly from ALS Principal Investigators (PIs) through customized data collection forms. Data provided by PIs will be reviewed by a Technical Task Monitor (TTM) before posting the information to OPIS for ALS Community viewing via the Web. Such Annual Reports will be permanent, citable references within OPIS. OPlS core functionality will also include Project Home Sites, which will allow PIS to provide updated technology information to the Community in between Annual Report updates. All data will be stored in an object-oriented relational database, created in MySQL(Reistered Trademark) and located on a secure server at NASA Ames Research Center (ARC). Upon launch, OPlS can be utilized by Managers to identify research and technology development (R&TD) gaps and to assess task performance. Analysts can employ OPlS to obtain the current, comprehensive, accurate information about advanced technologies that is required to perform trade studies of various life support system options. ALS researchers and technology developers can use OPlS to achieve an improved understanding of the NASA and ALS Program needs and to understand how other researchers and technology developers are addressing those needs. OPlS core functionality will launch for 'Ihe ALS Program in October, 2005. However, the system has been developed with the ability to evolve with Program needs. Because of open-source construction, software costs are minimized. Any functionality that is technologically feasible can be built into OPIS, and OPlS can expand through module cloning and adaptation, to any level deemed useful to the Agency.

Skin and Eye Irritation Assessment of Oil Palm ( Elaeis guineensis) Leaf Extract for Topical Application.

PubMed

Yusof, Nor Zuliana; Abd Gani, Siti Salwa; Azizul Hasan, Zafarizal Aldrin; Idris, Zainab

2018-01-01

Many types of phytochemicals have been found to be present in oil palm leaf and could potentially be used as functional ingredients for skincare product. However, as of today, there is no published report on hazard identification and safety assessment of oil palm ( Elaeis guineensis) leaf extract (OPLE), particularly on skin and eye irritation. In this study, potential hazard of OPLE on skin and eye irritation was evaluated as an initial step to the safety assessment of OPLE. In vitro cell viability study of OPLE on normal human dermal fibroblasts showed that OPLE was nontoxic to the cells with percentage viability more than 90% after 24 and 48 hours of incubation. Skin irritation potential of OPLE was evaluated using in vitro SkinEthic reconstructed human epidermis (RHE) model (Organization for Economic Cooperation and Development [OECD] Test Guideline 439, 2015), while eye irritation potential was evaluated using in vitro SkinEthic Human corneal epithelium (HCE) model (OECD test guideline 492, 2017). Hazard identification results showed that OPLE at 1%, 5%, and 10% (wt/wt) was classified as nonirritant to the skin and eye where mean tissue viabilities of SkinEthic RHE and SkinEthic HCE were more than 50% and 60%, respectively. Therefore, we recommend a further safety assessment, such as human patch testing, to confirm the nonirritant of OPLE.

The OPL Sourcebook: A Guide for Solo and Small Libraries.

ERIC Educational Resources Information Center

Siess, Judith A.

Taking an international approach to reflect the growing number of one-person libraries (OPLs) worldwide, this handbook and directory for OPLs covers organizational culture, customer service, time management and planning, budgeting, accounting, technology, collection development, education, downsizing, outsourcing, and many other key management…

Relationships between POPs, biometrics and circulating steroids in male polar bears (Ursus maritimus) from Svalbard.

PubMed

Ciesielski, Tomasz M; Hansen, Ingunn Tjelta; Bytingsvik, Jenny; Hansen, Martin; Lie, Elisabeth; Aars, Jon; Jenssen, Bjørn M; Styrishave, Bjarne

2017-11-01

The aim of this study was to determine the effects of persistent organic pollutants (POPs) and biometric variables on circulating levels of steroid hormones (androgens, estrogens and progestagens) in male polar bears (Ursus maritimus) from Svalbard, Norway (n = 23). Levels of pregnenolone (PRE), progesterone (PRO), androstenedione (AN), dehydroepiandrosterone (DHEA), testosterone (TS), dihydrotestosterone (DHT), estrone (E1), 17α-estradiol (αE2) and 17β-estradiol (βE2) were quantified in polar bear serum by gas chromatography tandem mass spectrometry (GC-MS/MS), while POPs were measured in plasma. Subsequently, associations between hormone concentrations (9 steroids), POPs (21 polychlorinated biphenyls (PCBs), 8 OH-PCBs, 8 organochlorine pesticides (OCPs) and OCP metabolites, and 2 polybrominated diphenyl ethers (PBDEs)) and biological variables (age, head length, body mass, girth, body condition index), capture date, location (latitude and longitude), lipid content and cholesterol levels were examined using principal component analysis (PCA) and orthogonal projections to latent structures (OPLS) modelling. Average concentrations of androgens, estrogens and progestagens were in the range of 0.57-83.7 (0.57-12.4 for subadults, 1.02-83.7 for adults), 0.09-2.69 and 0.57-2.44 nmol/L, respectively. The steroid profiles suggest that sex steroids were mainly synthesized through the Δ-4 pathway in male polar bears. The ratio between androgens and estrogens significantly depended on sexual maturity with androgen/estrogen ratios being approximately 60 times higher in adult males than in subadult males. PCA plots and OPLS models indicated that TS was positively related to biometrics, such as body condition index in male polar bears. A negative relationship was also observed between POPs and DHT. Consequently, POPs and body condition may potentially affect the endocrinological function of steroids, including development of reproductive tissues and sex organs and the general condition of male polar bears. Copyright © 2017 Elsevier Ltd. All rights reserved.

New Force Field Model for Propylene Glycol: Insight to Local Structure and Dynamics.

PubMed

Ferreira, Elisabete S C; Voroshylova, Iuliia V; Koverga, Volodymyr A; Pereira, Carlos M; Cordeiro, M Natália D S

2017-12-07

In this work we developed a new force field model (FFM) for propylene glycol (PG) based on the OPLS all-atom potential. The OPLS potential was refined using quantum chemical calculations, taking into account the densities and self-diffusion coefficients. The validation of this new FFM was carried out based on a wide range of physicochemical properties, such as density, enthalpy of vaporization, self-diffusion coefficients, isothermal compressibility, surface tension, and shear viscosity. The molecular dynamics (MD) simulations were performed over a large range of temperatures (293.15-373.15 K). The comparison with other force field models, such as OPLS, CHARMM27, and GAFF, revealed a large improvement of the results, allowing a better agreement with experimental data. Specific structural properties (radial distribution functions, hydrogen bonding and spatial distribution functions) were then analyzed in order to support the adequacy of the proposed FFM. Pure propylene glycol forms a continuous phase, displaying no microstructures. It is shown that the developed FFM gives rise to suitable results not only for pure propylene glycol but also for mixtures by testing its behavior for a 50 mol % aqueous propylene glycol solution. Furthermore, it is demonstrated that the addition of water to the PG phase produces a homogeneous solution and that the hydration interactions prevail over the propylene glycol self-association interactions.

NMR Metabolomics Investigates the Influence of Flavonoid-Enriched Rations on Chicken Plasma.

PubMed

Fotakis, Charalambos; Lantzouraki, Dimitra Z; Goliomytis, Michael; Simitzis, Panagiotis E; Charismiadou, Maria; Deligeorgis, Stelios G; Zoumpoulakis, Panagiotis

2017-03-01

The use of flavonoids as dietary supplements is well established, mainly due to their intense antioxidant and anti-inflammatory properties. In the present study, hesperidin, naringin, and vitamin E were used as additives at different concentrations in poultry rations in order to achieve meat of improved quality. NMR metabolomics was applied to chicken blood serum samples to discern whether and how the enriched rations affected the animals' metabolic profile. Variations in the metabolic patterns according to sustenance consumption were traced by orthogonal projections to latent structures discriminant analysis (OPLS-DA) models and were attributed to specific metabolites by using S-line plots. In particular, serum samples from chickens fed with vitamin E displayed higher concentrations of glycine and succinic acid compared to control samples, which were mainly characterized by betaine, formic acid, and lipoproteins. Samples from chickens fed with hesperidin were characterized by increased levels of lactic acid, citric acid, creatine, carnosine, creatinine, phosphocreatine, anserine, glucose, and alanine compared to control samples. Lastly, naringin samples exhibited increased levels of citric and acetic acids. Results verify the scalability of NMR metabolomics to highlight metabolite variations among chicken serum samples in relation to food rations.

An HR-MAS MR Metabolomics Study on Breast Tissues Obtained with Core Needle Biopsy

PubMed Central

Cho, Nariya; Chang, Jung Min; Koo, Hye Ryoung; Yi, Ann; Kim, Hyeonjin; Park, Sunghyouk; Moon, Woo Kyung

2011-01-01

Background Much research has been devoted to the development of new breast cancer diagnostic measures, including those involving high-resolution magic angle spinning (HR-MAS) magnetic resonance (MR) spectroscopic techniques. Previous HR-MAS MR results have been obtained from post-surgery samples, which limits their direct clinical applicability. Methodology/Principal Findings In the present study, we performed HR-MAS MR spectroscopic studies on 31 breast tissue samples (13 cancer and 18 non-cancer) obtained by percutaneous core needle biopsy. We showed that cancer and non-cancer samples can be discriminated very well with Orthogonal Projections to Latent Structure-Discriminant Analysis (OPLS-DA) multivariate model on the MR spectra. A subsequent blind test showed 69% sensitivity and 94% specificity in the prediction of the cancer status. A spectral analysis showed that in cancer cells, taurine- and choline-containing compounds are elevated. Our approach, additionally, could predict the progesterone receptor statuses of the cancer patients. Conclusions/Significance HR-MAS MR metabolomics on intact breast tissues obtained by core needle biopsy may have a potential to be used as a complement to the current diagnostic and prognostic measures for breast cancers. PMID:22028780

Atomistic Molecular Dynamics Simulations of Carbon Dioxide Diffusivity in n-Hexane, n-Decane, n-Hexadecane, Cyclohexane, and Squalane.

PubMed

Moultos, Othonas A; Tsimpanogiannis, Ioannis N; Panagiotopoulos, Athanassios Z; Trusler, J P Martin; Economou, Ioannis G

2016-12-22

Atomistic molecular dynamics simulations were carried out to obtain the diffusion coefficients of CO 2 in n-hexane, n-decane, n-hexadecane, cyclohexane, and squalane at temperatures up to 423.15 K and pressures up to 65 MPa. Three popular models were used for the representation of hydrocarbons: the united atom TraPPE (TraPPE-UA), the all-atom OPLS, and an optimized version of OPLS, namely, L-OPLS. All models qualitatively reproduce the pressure dependence of the diffusion coefficient of CO 2 in hydrocarbons measured recently, and L-OPLS was found to be the most accurate. Specifically for n-alkanes, L-OPLS also reproduced the measured viscosities and densities much more accurately than the original OPLS and TraPPE-UA models, indicating that the optimization of the torsional potential is crucial for the accurate description of transport properties of long chain molecules. The three force fields predict different microscopic properties such as the mean square radius of gyration for the n-alkane molecules and pair correlation functions for the CO 2 -n-alkane interactions. CO 2 diffusion coefficients in all hydrocarbons studied are shown to deviate significantly from the Stokes-Einstein behavior.

Improved treatment of nucleosides and nucleotides in the OPLS-AA force field

NASA Astrophysics Data System (ADS)

Robertson, Michael J.; Tirado-Rives, Julian; Jorgensen, William L.

2017-09-01

DFT calculations have been used to develop improved descriptions of the torsional energetics for nucleosides and nucleotides in the OPLS-AA force field. Scans of nucleotide dihedral angles (γ, χ, and β) and methyl phosphates provided the bases for the new torsional parameters. In addition, the angle-bending parameters of phosphodiesters and ribose were updated, and adjustments were made to existing carbohydrate torsions to better capture the sugar puckering landscape of ribose. MD simulations of nucleosides with the new parameters demonstrate a significant improvement in the ribose sugar puckering and χ angle distributions. Additionally, energy-minimization of protein-nucleotide crystal structures with the new parameters produced accurate poses.

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

Rosenman, David J.; Wang, Chunyu; García, Angel E.

We found that amyloid β (Aβ) monomers represent a base state in the pathways of aggregation that result in the fibrils and oligomers implicated in the pathogenesis of Alzheimer’s disease (AD). The structural properties of these intrinsically disordered peptides remain unclear despite extensive experimental and computational investigations. Further, there are mutations within Aβ that change the way the peptide aggregates and are known to cause familial AD (FAD). Here, we analyze the ensembles of different isoforms (Aβ42 and Aβ40) and mutants (E22Δ, D23N, E22K, E22G, and A2T in Aβ40) of Aβ generated with all-atom replica exchange molecular dynamics (REMD) simulationsmore » on the μs/replica time scale. These were run using three different force field/water model combinations: OPLS-AA/L and TIP3P (“OPLS”), AMBER99sb-ILDN and TIP4P-Ew (“ILDN”), as well as CHARMM22* and TIP3SP (“CHARMM”). Despite fundamental changes in simulation parameters, we find that the resulting ensembles demonstrate a strong convergence in structural properties. In particular, antiparallel contacts between L17–A21 and A30–L34 are prevalent in ensembles of Aβ40, directly forming β sheets in the OPLS and ILDN combinations. A21–A30 commonly forms an interceding region that rarely interacts with the rest of the peptide. Further, Aβ42 contributes new β hairpin motifs involving V40–I41 in both OPLS and ILDN. However, the structural flexibility of the central region and the electrostatic interactions that characterize it are notably different between the different conditions. Further, for OPLS, each of the FAD mutations disrupts central bend character and increases the polymorphism of antiparallel contacts across the central region. However, the studied mutations in the ILDN set primarily encourage more global contacts involving the N-terminus and the central region, and promote the formation of new β topologies that may seed different aggregates involved in disease phenotypes. Furthermore, these differences aside, the large degree of agreement between simulation sets across multiple force fields provides a generalizable characterization of Aβ that is also consistent with experimental data and models.« less

Structural features of small benzene clusters (C6H6)n (n ≤ 30) as investigated with the all-atom OPLS potential.

PubMed

Takeuchi, Hiroshi

2012-10-18

The structures of the simplest aromatic clusters, benzene clusters (C(6)H(6))(n), are not well elucidated. In the present study, benzene clusters (C(6)H(6))(n) (n ≤ 30) were investigated with the all-atom optimized parameters for liquid simulation (OPLS) potential. The global minima and low-lying minima of the benzene clusters were searched with the heuristic method combined with geometrical perturbations. The structural features and growth sequence of the clusters were examined by carrying out local structure analyses and structural similarity evaluation with rotational constants. Because of the anisotropic interaction between the benzene molecules, the local structures consisting of 13 molecules are considerably deviated from regular icosahedron, and the geometries of some of the clusters are inconsistent with the shapes constructed by the interior molecules. The distribution of the angle between the lines normal to two neighboring benzene rings is anisotropic in the clusters, whereas that in the liquid benzene is nearly isotropic. The geometries and energies of the low-lying configurations and the saddle points between them suggest that most of the configurations previously detected in supersonic expansions take different orientations for one to four neighboring molecules.

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

Vener, M. V., E-mail: mikhail.vener@gmail.com; Odinokov, A. V.; Wehmeyer, C.

Salt bridges and ionic interactions play an important role in protein stability, protein-protein interactions, and protein folding. Here, we provide the classical MD simulations of the structure and IR signatures of the arginine (Arg)–glutamate (Glu) salt bridge. The Arg-Glu model is based on the infinite polyalanine antiparallel two-stranded β-sheet structure. The 1 μs NPT simulations show that it preferably exists as a salt bridge (a contact ion pair). Bidentate (the end-on and side-on structures) and monodentate (the backside structure) configurations are localized [Donald et al., Proteins 79, 898–915 (2011)]. These structures are stabilized by the short {sup +}N–H⋯O{sup −} bonds.more » Their relative stability depends on a force field used in the MD simulations. The side-on structure is the most stable in terms of the OPLS-AA force field. If AMBER ff99SB-ILDN is used, the backside structure is the most stable. Compared with experimental data, simulations using the OPLS all-atom (OPLS-AA) force field describe the stability of the salt bridge structures quite realistically. It decreases in the following order: side-on > end-on > backside. The most stable side-on structure lives several nanoseconds. The less stable backside structure exists a few tenth of a nanosecond. Several short-living species (solvent shared, completely separately solvated ionic groups ion pairs, etc.) are also localized. Their lifetime is a few tens of picoseconds or less. Conformational flexibility of amino acids forming the salt bridge is investigated. The spectral signature of the Arg-Glu salt bridge is the IR-intensive band around 2200 cm{sup −1}. It is caused by the asymmetric stretching vibrations of the {sup +}N–H⋯O{sup −} fragment. Result of the present paper suggests that infrared spectroscopy in the 2000–2800 frequency region may be a rapid and quantitative method for the study of salt bridges in peptides and ionic interactions between proteins. This region is usually not considered in spectroscopic studies of peptides and proteins.« less

Accuracy Test of the OPLS-AA Force Field for Calculating Free Energies of Mixing and Comparison with PAC-MAC

PubMed Central

2017-01-01

We have calculated the excess free energy of mixing of 1053 binary mixtures with the OPLS-AA force field using two different methods: thermodynamic integration (TI) of molecular dynamics simulations and the Pair Configuration to Molecular Activity Coefficient (PAC-MAC) method. PAC-MAC is a force field based quasi-chemical method for predicting miscibility properties of various binary mixtures. The TI calculations yield a root mean squared error (RMSE) compared to experimental data of 0.132 kBT (0.37 kJ/mol). PAC-MAC shows a RMSE of 0.151 kBT with a calculation speed being potentially 1.0 × 104 times greater than TI. OPLS-AA force field parameters are optimized using PAC-MAC based on vapor–liquid equilibrium data, instead of enthalpies of vaporization or densities. The RMSE of PAC-MAC is reduced to 0.099 kBT by optimizing 50 force field parameters. The resulting OPLS-PM force field has a comparable accuracy as the OPLS-AA force field in the calculation of mixing free energies using TI. PMID:28418655

Aero-Optical Wavefront Propagation and Refractive Fluid Interfaces in Large-Reynolds-Number Compressible Turbulent Flows

DTIC Science & Technology

2005-12-31

are utilized with the eikonal equation of geometrical optics to propagate computationally the optical wavefronts in the near field. As long as the...aero-optical interactions. In terms of the refractive index field n and the optical path length (OPL), the eikonal equation is: |∇ (OPL)| = n , (9) (e.g...ray n(`, t) d` . (10) The OPL integral corresponds to inverting the eikonal equation 9. The physical distance along the beam propagation path for

Metabolic Footprinting of Fermented Milk Consumption in Serum of Healthy Men

PubMed Central

Pimentel, Grégory; Burton, Kathryn J; von Ah, Ueli; Bütikofer, Ueli; Pralong, François P; Vionnet, Nathalie; Portmann, Reto; Vergères, Guy

2018-01-01

Abstract Background Fermentation is a widely used method of natural food preservation that has consequences on the nutritional value of the transformed food. Fermented dairy products are increasingly investigated in view of their ability to exert health benefits beyond their nutritional qualities. Objective To explore the mechanisms underpinning the health benefits of fermented dairy intake, the present study followed the effects of milk fermentation, from changes in the product metabolome to consequences on the human serum metabolome after its ingestion. Methods A randomized crossover study design was conducted in 14 healthy men [mean age: 24.6 y; mean body mass index (in kg/m2): 21.8]. At the beginning of each test phase, serum samples were taken 6 h postprandially after the ingestion of 800 g of a nonfermented milk or a probiotic yogurt. During the 2-wk test phases, subjects consumed 400 g of the assigned test product daily (200 g, 2 times/d). Serum samples were taken from fasting participants at the end of each test phase. The serum metabolome was assessed through the use of LC-MS–based untargeted metabolomics. Results Postprandial serum metabolomes after milk or yogurt intake could be differentiated [orthogonal projections to latent structures discriminant analysis (OPLS-DA) Q2 = 0.74]. Yogurt intake was characterized by higher concentrations of 7 free amino acids (including proline, P = 0.03), reduced concentrations of 5 bile acids (including glycocholic acid, P = 0.04), and modulation of 4 indole derivative compounds (including indole lactic acid, P = 0.01). Fasting serum samples after 2 wk of daily intake of milk or yogurt could also be differentiated based on their metabolic profiles (OPLS-DA Q2 = 0.56) and were discussed in light of the postprandial results. Conclusion Metabolic pathways related to amino acids, indole derivatives, and bile acids were modulated in healthy men by the intake of yogurt. Further investigation to explore novel health effects of fermented dairy products is warranted.This trial was registered at clinicaltrials.gov as NCT02230345. PMID:29788433

Chlorogenic Acids Biosynthesis in Centella asiatica Cells Is not Stimulated by Salicylic Acid Manipulation.

PubMed

Ncube, E N; Steenkamp, P A; Madala, N E; Dubery, I A

2016-07-01

Exogenous application of synthetic and natural elicitors of plant defence has been shown to result in mass production of secondary metabolites with nutraceuticals properties in cultured cells. In particular, salicylic acid (SA) treatment has been reported to induce the production of phenylpropanoids, including cinnamic acid derivatives bound to quinic acid (chlorogenic acids). Centella asiatica is an important medicinal plant with several therapeutic properties owing to its wide spectrum of secondary metabolites. We investigated the effect of SA on C. asiatica cells by monitoring perturbation of chlorogenic acids in particular. Different concentrations of SA were used to treat C. asiatica cells, and extracts from both treated and untreated cells were analysed using an optimised UHPLC-QTOF-MS/MS method. Semi-targeted multivariate data analyses with the aid of principal component analysis (PCA) and orthogonal projection to latent structures-discriminant analysis (OPLS-DA) revealed a concentration-dependent metabolic response. Surprisingly, a range of chlorogenic acid derivatives were found to be downregulated as a consequence of SA treatment. Moreover, irbic acid (3,5-O-dicaffeoyl-4-O-malonilquinic acid) was found to be a dominant CGA in C. asiatica cells, although the SA treatment also had a negative effect on its concentration. Overall SA treatment was found to be an ineffective elicitor of CGA production in cultured C. asiatica cells.

Urinary metabonomics study on toxicity biomarker discovery in rats treated with Xanthii Fructus.

PubMed

Lu, Fang; Cao, Min; Wu, Bin; Li, Xu-zhao; Liu, Hong-yu; Chen, Da-zhong; Liu, Shu-min

2013-08-26

Xanthii Fructus (XF) is commonly called "Cang-Erzi" in traditional Chinese medicine (TCM) and widely used for the treatment of sinusitis, headache, rheumatism, and skin itching. However, the clinical utilization of XF is relatively restricted owing to its toxicity. To discover the characteristic potential biomarkers in rats treated with XF by urinary metabonomics. Ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC-QTOF-MS) was applied in the study. The total ion chromatograms obtained from control and different dosage groups were distinguishable by a multivariate statistical analysis method. The greatest difference in metabolic profile was observed between high dosage group and control group, and the metabolic characters in rats treated with XF were perturbed in a dose-dependent manner. The metabolic changes in response for XF treatment were observed in urinary samples, which were revealed by orthogonal projection to latent structures discriminate analysis (OPLS-DA), and 10 metabolites could be served as the potential toxicity biomarkers. In addition, the mechanism associated with the damages of lipid per-oxidation and the metabolic disturbances of fatty acid oxidation were investigated. These results indicate that metabonomics analysis in urinary samples may be useful for predicting the toxicity induced by XF. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Changes in plasma protein levels as an early indication of a bloodstream infection

PubMed Central

Joenväärä, Sakari; Kaartinen, Johanna; Järvinen, Asko; Renkonen, Risto

2017-01-01

Blood culture is the primary diagnostic test performed in a suspicion of bloodstream infection to detect the presence of microorganisms and direct the treatment. However, blood culture is slow and time consuming method to detect blood stream infections or separate septic and/or bacteremic patients from others with less serious febrile disease. Plasma proteomics, despite its challenges, remains an important source for early biomarkers for systemic diseases and might show changes before direct evidence from bacteria can be obtained. We have performed a plasma proteomic analysis, simultaneously at the time of blood culture sampling from ten blood culture positive and ten blood culture negative patients, and quantified 172 proteins with two or more unique peptides. Principal components analysis, Orthogonal Projections to Latent Structures Discriminant Analysis (OPLS-DA) and ROC curve analysis were performed to select protein(s) features which can classify the two groups of samples. We propose a number of candidates which qualify as potential biomarkers to select the blood culture positive cases from negative ones. Pathway analysis by two methods revealed complement activation, phagocytosis pathway and alterations in lipid metabolism as enriched pathways which are relevant for the condition. Data are available via ProteomeXchange with identifier PXD005022. PMID:28235076

Identification of potential metabolic biomarkers of cerebrospinal fluids that differentiate tuberculous meningitis from other types of meningitis by a metabolomics study

PubMed Central

Dai, Yi-Ning; Huang, Hai-Jun; Song, Wen-Yuan; Tong, Yong-Xi; Yang, Dan-Hong; Wang, Ming-Shan; Huang, Yi-Cheng; Chen, Mei-Juan; Zhang, Jia-Jie; Ren, Ze-Ze; Zheng, Wei; Pan, Hong-Ying

2017-01-01

Tuberculous meningitis (TBM) is caused by tuberculosis infection of of the meninges, which are the membrane systems that encircle the brain, with a high morbidity and mortality rate. It is challenging to diagnose TBM among other types of meningitis, such as viral meningitis, bacterial meningitis and cryptococcal meningitis. We aimed to identify metabolites that are differentially expressed between TBM and the other types of meningitis by a global metabolomics analysis. The cerebrospinal fluids (CSF) from 50 patients with TBM, 17 with viral meningitis, 17 with bacterial meningitis, and 16 with cryptococcal meningitis were analyzed using ultra high performance liquid chromatography coupled with quadrupole time of flight mass spectrometry (UHPLC-QTOF-MS). A total of 1161 and 512 features were determined in positive and negative electrospray ionization mode, respectively. A clear separation between TBM and viral, bacterial or cryptococcal meningitis was achieved by orthogonal projections to latent structures-discriminate analysis (OPLS-DA) analysis. Potential metabolic markers and related pathways were identified, which were mainly involved in the metabolism of amino acid, lipids and nucleosides. In summary, differential metabolic profiles of the CSF exist between TBM and other types of meningitis, and potential metabolic biomarkers were identified to differentiate TBM from other types of meningitis. PMID:29245963

Molecular Model for HNBR with Tunable Cross-Link Density.

PubMed

Molinari, N; Khawaja, M; Sutton, A P; Mostofi, A A

2016-12-15

We introduce a chemically inspired, all-atom model of hydrogenated nitrile butadiene rubber (HNBR) and assess its performance by computing the mass density and glass-transition temperature as a function of cross-link density in the structure. Our HNBR structures are created by a procedure that mimics the real process used to produce HNBR, that is, saturation of the carbon-carbon double bonds in NBR, either by hydrogenation or by cross-linking. The atomic interactions are described by the all-atom "Optimized Potentials for Liquid Simulations" (OPLS-AA). In this paper, first, we assess the use of OPLS-AA in our models, especially using NBR bulk properties, and second, we evaluate the validity of the proposed model for HNBR by investigating mass density and glass transition as a function of the tunable cross-link density. Experimental densities are reproduced within 3% for both elastomers, and qualitatively correct trends in the glass-transition temperature as a function of monomer composition and cross-link density are obtained.

Using ILOG OPL-CPLEX and ILOG Optimization Decision Manager (ODM) to Develop Better Models

NASA Astrophysics Data System (ADS)

2008-10-01

This session will provide an in-depth overview on building state-of-the-art decision support applications and models. You will learn how to harness the full power of the ILOG OPL-CPLEX-ODM Development System (ODMS) to develop optimization models and decision support applications that solve complex problems ranging from near real-time scheduling to long-term strategic planning. We will demonstrate how to use ILOG's Open Programming Language (OPL) to quickly model problems solved by ILOG CPLEX, and how to use ILOG ODM to gain further insight about the model. By the end of the session, attendees will understand how to take advantage of the powerful combination of ILOG OPL (to describe an optimization model) and ILOG ODM (to understand the relationships between data, decision variables and constraints).

The optics of occupational progressive lenses.

PubMed

Sheedy, James E; Hardy, Raymond F

2005-08-01

Occupational progressive lenses (OPLs) utilize progressive power optics and are designed primarily to meet near and intermediate viewing needs such as working at a computer workstation for presbyopic patients. OPLs are fabricated to have the prescribed near power in the lower part of the lens and the power in the upper portion of the lens is determined by the amount of power "degression" (decrease in plus power) relative to the near power. Independent measurements of the optical characteristics of these lenses have not been reported previously. Manufacturers of 7 different OPL designs provided sample lenses for a patient with +2.50 D add that were measured with a Rotlex Class Plus lens analyzer (Rotlex Inc., Israel). Power measurements were normalized to the location specified by the manufacturer, and the vertical location of each lens was normalized to pupil center based on manufacturer fitting guidelines. Large optical differences exist among the OPL designs. The results show clear differences between the designs in terms of the add powers, their vertical location, and zone width. The size and location of the near, near-intermediate, far-intermediate, and far viewing zones were determined. The literature and clinical experience support that OPLs are successful at meeting the computer, general office, and other intermediate viewing distance needs of many patients. However, because of the large differences in the several OPL designs, patient success can likely be enhanced by selecting the design that best suits his or her viewing needs.

Characterization of Aβ Monomers through the Convergence of Ensemble Properties among Simulations with Multiple Force Fields

DOE PAGES

Rosenman, David J.; Wang, Chunyu; García, Angel E.

2016-01-12

We found that amyloid β (Aβ) monomers represent a base state in the pathways of aggregation that result in the fibrils and oligomers implicated in the pathogenesis of Alzheimer’s disease (AD). The structural properties of these intrinsically disordered peptides remain unclear despite extensive experimental and computational investigations. Further, there are mutations within Aβ that change the way the peptide aggregates and are known to cause familial AD (FAD). Here, we analyze the ensembles of different isoforms (Aβ42 and Aβ40) and mutants (E22Δ, D23N, E22K, E22G, and A2T in Aβ40) of Aβ generated with all-atom replica exchange molecular dynamics (REMD) simulationsmore » on the μs/replica time scale. These were run using three different force field/water model combinations: OPLS-AA/L and TIP3P (“OPLS”), AMBER99sb-ILDN and TIP4P-Ew (“ILDN”), as well as CHARMM22* and TIP3SP (“CHARMM”). Despite fundamental changes in simulation parameters, we find that the resulting ensembles demonstrate a strong convergence in structural properties. In particular, antiparallel contacts between L17–A21 and A30–L34 are prevalent in ensembles of Aβ40, directly forming β sheets in the OPLS and ILDN combinations. A21–A30 commonly forms an interceding region that rarely interacts with the rest of the peptide. Further, Aβ42 contributes new β hairpin motifs involving V40–I41 in both OPLS and ILDN. However, the structural flexibility of the central region and the electrostatic interactions that characterize it are notably different between the different conditions. Further, for OPLS, each of the FAD mutations disrupts central bend character and increases the polymorphism of antiparallel contacts across the central region. However, the studied mutations in the ILDN set primarily encourage more global contacts involving the N-terminus and the central region, and promote the formation of new β topologies that may seed different aggregates involved in disease phenotypes. Furthermore, these differences aside, the large degree of agreement between simulation sets across multiple force fields provides a generalizable characterization of Aβ that is also consistent with experimental data and models.« less

Teratology of 2,3,7,8-tetrachlorodibenzo-p-dioxin in a complex environmental mixture from the Love Canal

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

Silkworth, J.B.; Cutler, D.S.; Antrim, L.

The organic phase of a leachate (OPL) from the Love Canal chemical dump site contains more than 100 organic compounds including 2,3,7,8-Tetrachlorodibenzo-p-dioxin (TCDD). The teratogenic potential of OPL was determined in two inbred and one hybrid mouse strain which differ in their sensitivity to aromatic hydrocarbon (Ah) receptor-mediated toxicity. OPL was orally administered in corn oil on Days 6-15 of gestation to C57BL/6J mice (Ahb/Ahb) at doses of 0, 0.1, 0.3, 0.5, and 0.7 g kg-1 day-1 and to DBA/2J (Ahd/Ahd) females, which were mated with either DBA/2J or C57BL/6J males, at 0, 0.5, 1, and 2.0 g kg-1 day-1.more » In C57BL/6J mice, which express a high-affinity Ah receptor that avidly binds TCDD, the ED50's of OPL for cleft palate and hydronephrosis were 0.44 and 0.11 g OPL kg-1 day-1, respectively. Maternal mortality was 5% at the highest dose. In DBA/2J fetuses, which express a low-affinity receptor, neither treatment-related cleft palate nor hydronephrosis was induced by dose levels that caused 36% maternal mortality. In hybrid D2B6F1 fetuses, the incidence of cleft palate reached only 8% at 2 g OPL kg-1 day-1 but the ED50 for hydronephrosis was 0.76 g OPL kg-1 day-1. TCDD was similarly administered to pregnant C57BL/6J mice at 0, 0.5, 1, 2, and 4 micrograms kg-1 day-1 and to DBA/2J mice at 0, 0.5, 2, 4, and 8 micrograms kg-1 day-1. In C57BL/6J fetuses, the ED50's for cleft palate and hydronephrosis were 4.6 and 0.73 microgram TCDD kg-1 day-1, respectively. In DBA/2J fetuses the ED50's for cleft palate and hydronephrosis were 15.0 and 6.4 micrograms TCDD kg-1 day-1, respectively. Both the OPL and TCDD caused maternal hepatomegaly and thymic atrophy in all strains, but increased only C57BL/6J fetal weights. OPL decreased the number of fetuses per C57BL/6J dam at the two highest doses but there were no other reproductive effects in any of the groups.« less

Characterization of an optimized light source and comparison to pulsed dye laser for superficial and deep vessel clearance.

PubMed

Weiss, Robert A; Ross, E Victor; Tanghetti, Emil A; Vasily, David B; Childs, James J; Smirnov, Mikhail Z; Altshuler, Gregory B

2011-02-01

An arc lamp-based device providing optimized spectrum and pulse shape was characterized and compared with two pulsed dye laser (PDL) systems using a vascular phantom. Safety and effectiveness for facial telangiectasia are presented in clinical case studies. An optimized pulsed light source's (OPL) spectral and power output were characterized and compared with two 595 nm PDL devices. Purpuric threshold fluences were determined for the OPL and PDLs on Fitzpatrick type II normal skin. A vascular phantom comprising blood-filled quartz capillaries beneath porcine skin was treated by the devices at their respective purpuric threshold fluences for 3 ms pulse widths, while vessel temperatures were monitored with an infrared (IR) camera. Patients with Fitzpatrick skin types II-III received a split-face treatment with the OPL and a 595 nm PDL. The OPL provided a dual-band output spectrum from 500 to 670 nm and 850-1,200 nm, pulse widths from 3 to 100 ms, and fluences to 80 J/cm(2). The smooth output power measured during all pulse widths provides unambiguous vessel size selectivity. Percent energy in the near infra-red increased with decreasing output power from 45% to 60% and contributed 15-26% to heating of deep vessels, respectively. At purpuric threshold fluences the ratio of OPL to PDL vessel temperature rise was 1.7-2.8. OPL treatments of facial telangiectasia were well-tolerated by patients demonstrating significant improvements comparable to PDL with no downtime. Intense pulsed light (IPL) and PDL output pulse and spectral profiles are important for selective treatment of vessels in vascular lesions. The OPL's margin between purpuric threshold fluence and treatment fluence for deeper, larger vessels was greater than the corresponding margin with PDLs. The results warrant further comparison studies with IPLs and other PDLs. Copyright © 2011 Wiley-Liss, Inc.

A new intermolecular potential for simulations of methanol: The OPLS/2016 model

NASA Astrophysics Data System (ADS)

Gonzalez-Salgado, D.; Vega, C.

2016-07-01

In this work, a new rigid-nonpolarizable model of methanol is proposed. The model has three sites, located at the same positions as those used in the OPLS model previously proposed by Jorgensen [J. Phys. Chem. 90, 1276 (1986)]. However, partial charges and the values of the Lennard-Jones parameters were modified by fitting to an adequately selected set of target properties including solid-fluid experimental data. The new model was denoted as OPLS/2016. The overall performance of this model was evaluated and compared to that obtained with other popular models of methanol using a similar test to that recently proposed for water models. In the test, a certain numerical score is given to each model. It was found that the OPLS/2016 obtained the highest score (7.4 of a maximum of 10) followed by L1 (6.6), L2 (6.4), OPLS (5.8), and H1 (3.5) models. The improvement of OPLS/2016 with respect to L1 and L2 is mainly due to an improvement in the description of fluid-solid equilibria (the melting point is only 14 K higher than the experimental value). In addition, it was found that no methanol model was able to reproduce the static dielectric constant and the isobaric heat capacity, whereas the better global performance was found for models that reproduce the vaporization enthalpy once the so-called polarization term is included. Similar conclusions were suggested previously in the analysis of water models and are confirmed here for methanol.

Optically Phase-Locked Electronic Speckle Pattern Interferometer (OPL-ESPI)

NASA Astrophysics Data System (ADS)

Moran, Steven E.; Law, Robert L.; Craig, Peter N.; Goldberg, Warren M.

1986-10-01

This report describes the design, theory, operation, and characteristics of the OPL-ESPI, which generates real time equal Doppler speckle contours of vibrating objects from unstable sensor platforms with a Doppler resolution of 30 Hz and a maximum tracking range of + or - 5 HMz. The optical phase locked loop compensates for the deleterious effects of ambient background vibration and provides the bases for a new ESPI video signal processing technique, which produces high contrast speckle contours. The OPL-ESPI system has local oscillator phase modulation capability, offering the potential for detection of vibrations with the amplitudes less than lambda/100.

Frontal-temporal synchronization of EEG signals quantified by order patterns cross recurrence analysis during propofol anesthesia.

PubMed

Shalbaf, Reza; Behnam, Hamid; Sleigh, Jamie W; Steyn-Ross, D Alistair; Steyn-Ross, Moira L

2015-05-01

Characterizing brain dynamics during anesthesia is a main current challenge in anesthesia study. Several single channel electroencephalogram (EEG)-based commercial monitors like the Bispectral index (BIS) have suggested to examine EEG signal. But, the BIS index has obtained numerous critiques. In this study, we evaluate the concentration-dependent effect of the propofol on long-range frontal-temporal synchronization of EEG signals collected from eight subjects during a controlled induction and recovery design. We used order patterns cross recurrence plot and provide an index named order pattern laminarity (OPL) to assess changes in neuronal synchronization as the mechanism forming the foundation of conscious perception. The prediction probability of 0.9 and 0.84 for OPL and BIS specified that the OPL index correlated more strongly with effect-site propofol concentration. Also, our new index makes faster reaction to transients in EEG recordings based on pharmacokinetic and pharmacodynamic model parameters and demonstrates less variability at the point of loss of consciousness (standard deviation of 0.04 for OPL compared with 0.09 for BIS index). The result show that the OPL index can estimate anesthetic state of patient more efficiently than the BIS index in lightly sedated state with more tolerant of artifacts.

Intermolecular Potentials of Methane Assessed by Second Virial Coefficients, ab Initio Dimer Interaction Energies, and Aggregate Cohesive Energies.

PubMed

Ribeiro, Douglas S

2017-06-01

This study presents computations of three energy related properties for 26 previously published multisite intermolecular potentials of methane: MM2, MM3, MM2en, MM3en, MM2mc, MM3mc, MM3envir, RMK, OPLS all-atom, MUB-2, AMBER, BOYD, Williams, Sheikh, MG, Tsuzuki, E2-Gay, E4-Gay, MP4exp-6(iii), MP4exp-6(iv), Rowley-A, Rowley-B, TraPPE-EH, Ouyang, CLC, and Chao and three united atom potentials: Saager-Fischer (SF), OPLS united atom, and HFD. The three properties analyzed are the second virial coefficients for 14 temperature points in the range of 110 to 623.15 K, the interaction energies for 12 orientations of the methane dimer as a function of distance followed by a comparison to three ab initio data sets and the cohesive energy of the aggregate of 512 methane molecules. The latter computed energies are correlated to latent heat of evaporation of 11 potentials and are proposed as surrogate approximate parameters for ΔH vap for the studied potentials. The 10 best performing potentials are selected by rms order in each one of the properties and three of them are found to be present simultaneously in the three sets: Tsuzuki, MM3mc, and MM2mc. On the basis of the cohesive energy of the aggregate, a quantitative measure of the anisotropy of the potentials is proposed. The results are discussed on the basis of anisotropy, nonadditivity and ability of the potentials to reproduce ab initio data. It is concluded that the nonadditivity of the pair potentials holds and the available ab initio data did not lead to pair potentials that are cohesive enough to reproduce accurately the second virial coefficients.

Tomographic Structural Changes of Retinal Layers after Internal Limiting Membrane Peeling for Macular Hole Surgery.

PubMed

Faria, Mun Yueh; Ferreira, Nuno P; Cristóvao, Diana M; Mano, Sofia; Sousa, David Cordeiro; Monteiro-Grillo, Manuel

2018-01-01

To highlight tomographic structural changes of retinal layers after internal limiting membrane (ILM) peeling in macular hole surgery. Nonrandomized prospective, interventional study in 38 eyes (34 patients) subjected to pars plana vitrectomy and ILM peeling for idiopathic macular hole. Retinal layers were assessed in nasal and temporal regions before and 6 months after surgery using spectral domain optical coherence tomography. Total retinal thickness increased in the nasal region and decreased in the temporal region. The retinal nerve fiber layer (RNFL), ganglion cell layer (GCL), and inner plexiform layer (IPL) showed thinning on both nasal and temporal sides of the fovea. The thickness of the outer plexiform layer (OPL) increased. The outer nuclear layer (ONL) and outer retinal layers (ORL) increased in thickness after surgery in both nasal and temporal regions. ILM peeling is associated with important alterations in the inner retinal layer architecture, with thinning of the RNFL-GCL-IPL complex and thickening of OPL, ONL, and ORL. These structural alterations can help explain functional outcome and could give indications regarding the extent of ILM peeling, even though peeling seems important for higher rate of hole closure. © 2017 S. Karger AG, Basel.

Oral Screening for Pre-cancerous Lesions Among Areca-nut Chewing Population from Rural India.

PubMed

Chatterjee, Ramdas; Gupta, Bhawna; Bose, Surojit

2015-01-01

To detect early oral premalignant lesions (OPLs) in a rural population chewing tobacco-free areca nut preparations, determine their awareness level of oral cancer and educate them about maintaining good oral health. A total of 2175 18- to 65-year-old areca nut chewers (male:female ratio 2.5:1), without a history of consuming tobacco in any form, from the villages of two districts of the West Bengal state of India were screened clinically through oral examination for suspected OPLs. A pre-designed questionnaire was employed to record demographic data, information on tobacco-free areca-nut chewing habit and knowledge about oral diseases. Education on oral health was provided through distribution of printed leaflets, display of banner/posters and a public-announcement system. Chewing areca nut in the form of betel quid was more popular (90.7%) than chewing areca nut alone (9%) or tobacco-free packaged areca nut preparation sold as 'pan masala' (0.3%). OPLs were detected in 7.3% of the subjects, more among the males. An increasing incidence of OPLs could be observed with an increase in age as well as with duration and frequency of areca-nut chewing, while decreasing incidence was observed with an increase in educational level. Oral submucous fibrosis showed the highest prevalence (2.7%) among the various OPLs detected. Tobacco-free areca-nut chewing is an independent risk factor for the development of OPL and a large rural population still practices such high risk behaviour. In rural areas with limited health care resources, screening by visual oral examination involving minimum cost may prove useful to reduce oral cancer mortality.

Improved Peptide and Protein Torsional Energetics with the OPLSAA Force Field.

PubMed

Robertson, Michael J; Tirado-Rives, Julian; Jorgensen, William L

2015-07-14

The development and validation of new peptide dihedral parameters are reported for the OPLS-AA force field. High accuracy quantum chemical methods were used to scan φ, ψ, χ1, and χ2 potential energy surfaces for blocked dipeptides. New Fourier coefficients for the dihedral angle terms of the OPLS-AA force field were fit to these surfaces, utilizing a Boltzmann-weighted error function and systematically examining the effects of weighting temperature. To prevent overfitting to the available data, a minimal number of new residue-specific and peptide-specific torsion terms were developed. Extensive experimental solution-phase and quantum chemical gas-phase benchmarks were used to assess the quality of the new parameters, named OPLS-AA/M, demonstrating significant improvement over previous OPLS-AA force fields. A Boltzmann weighting temperature of 2000 K was determined to be optimal for fitting the new Fourier coefficients for dihedral angle parameters. Conclusions are drawn from the results for best practices for developing new torsion parameters for protein force fields.

Unlocking interpretation in near infrared multivariate calibrations by orthogonal partial least squares.

PubMed

Stenlund, Hans; Johansson, Erik; Gottfries, Johan; Trygg, Johan

2009-01-01

Near infrared spectroscopy (NIR) was developed primarily for applications such as the quantitative determination of nutrients in the agricultural and food industries. Examples include the determination of water, protein, and fat within complex samples such as grain and milk. Because of its useful properties, NIR analysis has spread to other areas such as chemistry and pharmaceutical production. NIR spectra consist of infrared overtones and combinations thereof, making interpretation of the results complicated. It can be very difficult to assign peaks to known constituents in the sample. Thus, multivariate analysis (MVA) has been crucial in translating spectral data into information, mainly for predictive purposes. Orthogonal partial least squares (OPLS), a new MVA method, has prediction and modeling properties similar to those of other MVA techniques, e.g., partial least squares (PLS), a method with a long history of use for the analysis of NIR data. OPLS provides an intrinsic algorithmic improvement for the interpretation of NIR data. In this report, four sets of NIR data were analyzed to demonstrate the improved interpretation provided by OPLS. The first two sets included simulated data to demonstrate the overall principles; the third set comprised a statistically replicated design of experiments (DoE), to demonstrate how instrumental difference could be accurately visualized and correctly attributed to Wood's anomaly phenomena; the fourth set was chosen to challenge the MVA by using data relating to powder mixing, a crucial step in the pharmaceutical industry prior to tabletting. Improved interpretation by OPLS was demonstrated for all four examples, as compared to alternative MVA approaches. It is expected that OPLS will be used mostly in applications where improved interpretation is crucial; one such area is process analytical technology (PAT). PAT involves fewer independent samples, i.e., batches, than would be associated with agricultural applications; in addition, the Food and Drug Administration (FDA) demands "process understanding" in PAT. Both these issues make OPLS the ideal tool for a multitude of NIR calibrations. In conclusion, OPLS leads to better interpretation of spectrometry data (e.g., NIR) and improved understanding facilitates cross-scientific communication. Such improved knowledge will decrease risk, with respect to both accuracy and precision, when using NIR for PAT applications.

Investigation of nuclear nano-morphology marker as a biomarker for cancer risk assessment using a mouse model

NASA Astrophysics Data System (ADS)

Bista, Rajan K.; Uttam, Shikhar; Hartman, Douglas J.; Qiu, Wei; Yu, Jian; Zhang, Lin; Brand, Randall E.; Liu, Yang

2012-06-01

The development of accurate and clinically applicable tools to assess cancer risk is essential to define candidates to undergo screening for early-stage cancers at a curable stage or provide a novel method to monitor chemoprevention treatments. With the use of our recently developed optical technology--spatial-domain low-coherence quantitative phase microscopy (SL-QPM), we have derived a novel optical biomarker characterized by structure-derived optical path length (OPL) properties from the cell nucleus on the standard histology and cytology specimens, which quantifies the nano-structural alterations within the cell nucleus at the nanoscale sensitivity, referred to as nano-morphology marker. The aim of this study is to evaluate the feasibility of the nuclear nano-morphology marker from histologically normal cells, extracted directly from the standard histology specimens, to detect early-stage carcinogenesis, assess cancer risk, and monitor the effect of chemopreventive treatment. We used a well-established mouse model of spontaneous carcinogenesis--ApcMin mice, which develop multiple intestinal adenomas (Min) due to a germline mutation in the adenomatous polyposis coli (Apc) gene. We found that the nuclear nano-morphology marker quantified by OPL detects the development of carcinogenesis from histologically normal intestinal epithelial cells, even at an early pre-adenomatous stage (six weeks). It also exhibits a good temporal correlation with the small intestine that parallels the development of carcinogenesis and cancer risk. To further assess its ability to monitor the efficacy of chemopreventive agents, we used an established chemopreventive agent, sulindac. The nuclear nano-morphology marker is reversed toward normal after a prolonged treatment. Therefore, our proof-of-concept study establishes the feasibility of the SL-QPM derived nuclear nano-morphology marker OPL as a promising, simple and clinically applicable biomarker for cancer risk assessment and evaluation of chemopreventive treatment.

Miniature Tunable Laser Spectrometer for Detection of a Trace Gas

NASA Technical Reports Server (NTRS)

Christensen, Lance E. (Inventor)

2017-01-01

An open-path laser spectrometer (OPLS) for measuring a concentration of a trace gas, the OPLS including an open-path multi-pass analysis region including a first mirror, a second mirror at a distance and orientation from the first mirror, and a support structure for locating the mirrors, a laser coupled to the analysis region and configured to emit light of a wavelength range and to enable a plurality of reflections of the emitted light between the mirrors, a detector coupled to the analysis region and configured to detect a portion of the emitted light impinging on the detector and to generate a corresponding signal, and an electronic system coupled to the laser and the detector, and configured to adjust the wavelength range of the emitted light from the laser based on the generated signal, and to measure the concentration of the trace gas based on the generated signal.

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

Freemark, M.; Comer, M.; Mularoni, T.

We have recently identified and purified from fetal liver a distinct receptor that mediates the effects of placental lactogen (PL) on amino acid transport, glycogen synthesis, and somatomedin production in fetal tissues. At present, the factors that regulate the number and affinity of PL receptors in the fetus are unknown. Since maternal nutrition plays a critical role in fetal metabolism and growth, we have examined the role of nutrition in the regulation of the PL receptor in fetal lambs. Pregnant ewes at 123-126 days gestation were fed ad libitum (FED), fasted for 3 days (FASTED), or fasted for 3 daysmore » and then refed for an additional 3 days (REFED). The ewes were then killed, and the binding of (125I)ovine (o) PL to hepatic microsomes from the fetal lambs was examined. Maternal fasting caused a 60-75% reduction in the specific binding of oPL to fetal liver; the effect of fasting was reversed in part by refeeding. The decrease in oPL binding resulted from an 80% reduction in the number of fetal oPL-binding sites (Scatchard analysis); there were no changes in the affinity of the oPL receptor (Kd, 0.6 nM), the subunit structure of the receptor, or the degree of occupancy of the receptor in vivo by endogenous fetal hormones. The specific bindings of GH (0.6%), PRL (0.3%), and insulin (35%) to fetal liver were not affected by maternal fasting, indicating that caloric restriction exerted a specific effect on oPL binding in the fetus. The number of fetal oPL-binding sites was positively correlated with the fetal liver glycogen content (r = 0.69; P less than 0.01) and the fetal plasma concentrations of glucose (r = 0.68; P less than 0.01) and insulin-like growth factor-I (r = 0.74; P less than 0.001), suggesting a role for the PL receptor in the regulation of fetal carbohydrate metabolism and growth.« less

Secondary metabolite perturbations in Phaseolus vulgaris leaves due to gamma radiation.

PubMed

Ramabulana, T; Mavunda, R D; Steenkamp, P A; Piater, L A; Dubery, I A; Madala, N E

2015-12-01

Oxidative stress is a condition in which the balance between the production and elimination of reactive oxygen species (ROS) is disturbed. However, plants have developed a very sophisticated mechanism to mitigate the effect of ROS by constantly adjusting the concentration thereof to acceptable levels. Electromagnetic radiation is one of the factors which results in oxidative stress. In the current study, ionizing gamma radiation generated from a Cobalt-60 source was used to induce oxidative stress in Phaseolus vulgaris seedlings. Plants were irradiated with several radiation doses, with 2 kGy found to be the optimal, non-lethal dose. Metabolite distribution patterns from irradiated and non-irradiated plants were analyzed using UHPLC-qTOF-MS and multivariate data models such as principal component analysis (PCA) and orthogonal projection to latent structures discriminate analysis (OPLS-DA). Metabolites such as hydroxycinnamic phenolic acids, flavonoids, terpenes, and a novel chalcone were found to be perturbed in P. vulgaris seedlings treated with the aforementioned conditions. The results suggest that there is a compensatory link between constitutive protectants and inducible responses to injury as well as defense against oxidative stress induced by ionizing radiation. The current study is also the first to illustrate the power of a metabolomics approach to decipher the effect of gamma radiation on crop plants. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

Metabolic dependence of green tea on plucking positions revisited: a metabolomic study.

PubMed

Lee, Jang-Eun; Lee, Bum-Jin; Hwang, Jeong-Ah; Ko, Kwang-Sup; Chung, Jin-Oh; Kim, Eun-Hee; Lee, Sang-Jun; Hong, Young-Shick

2011-10-12

The dependence of global green tea metabolome on plucking positions was investigated through (1)H nuclear magnetic resonance (NMR) analysis coupled with multivariate statistical data set. Pattern recognition methods, such as principal component analysis (PCA) and orthogonal projection on latent structure-discriminant analysis (OPLS-DA), were employed for a finding metabolic discrimination among fresh green tea leaves plucked at different positions from young to old leaves. In addition to clear metabolic discrimination among green tea leaves, elevations in theanine, caffeine, and gallic acid levels but reductions in catechins, such as epicatechin (EC), epigallocatechin (EGC), epicatechin-3-gallate (ECG), and epigallocatechin-3-gallate (EGCG), glucose, and sucrose levels were observed, as the green tea plant grows up. On the other hand, the younger the green tea leaf is, the more theanine, caffeine, and gallic acid but the lesser catechins accumlated in the green tea leaf, revealing a reverse assocation between theanine and catechins levels due to incorporaton of theanine into catechins with growing up green tea plant. Moreover, as compared to the tea leaf, the observation of marked high levels of theanine and low levels of catechins in green tea stems exhibited a distinct tea plant metabolism between the tea leaf and the stem. This metabolomic approach highlights taking insight to global metabolic dependence of green tea leaf on plucking position, thereby providing distinct information on green tea production with specific tea quality.

Metabolite Profiling Reveals Developmental Inequalities in Pinot Noir Berry Tissues Late in Ripening.

PubMed

Vondras, Amanda M; Commisso, Mauro; Guzzo, Flavia; Deluc, Laurent G

2017-01-01

Uneven ripening in Vitis vinifera is increasingly recognized as a phenomenon of interest, with substantial implications for fruit and wine composition and quality. This study sought to determine whether variation late in ripening (∼Modified Eichhorn-Lorenz stage 39) was associated with developmental differences that were observable as fruits within a cluster initiated ripening (véraison). Four developmentally distinct ripening classes of berries were tagged at cluster véraison, sampled at three times late in ripening, and subjected to untargeted HPLC-MS to measure variation in amino acids, sugars, organic acids, and phenolic metabolites in skin, pulp, and seed tissues separately. Variability was described using predominantly two strategies. In the first, multivariate analysis (Orthogonal Projections to Latent Structures-Discriminant Analysis, OPLS-DA) was used to determine whether fruits were still distinguishable per their developmental position at véraison and to identify which metabolites accounted for these distinctions. The same technique was used to assess changes in each tissue over time. In a second strategy and for each annotated metabolite, the variance across the ripening classes at each time point was measured to show whether intra-cluster variance (ICV) was growing, shrinking, or constant over the period observed. Indeed, berries could be segregated by OPLS-DA late in ripening based on their developmental position at véraison, though the four ripening classes were aggregated into two larger ripening groups. Further, not all tissues were dynamic over the period examined. Although pulp tissues could be segregated by time sampled, this was not true for seed and only moderately so for skin. Ripening group differences in seed and skin, rather than the time fruit was sampled, were better able to define berries. Metabolites also experienced significant reductions in ICV between single pairs of time points, but never across the entire experiment. Metabolites often exhibited a combination of ICV expansion, contraction and persistence. Finally, we observed significant differences in the abundance of some metabolites between ripening classes that suggest the berries that initiated ripening first remained developmentally ahead of the lagging fruit even late in the ripening phase. This presents a challenge to producers who would seek to harvest at uniformity or at a predefined level of variation.

Urinary metabonomic study of Panax ginseng in deficiency of vital energy rat using ultra performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry.

PubMed

Lin, He; Pi, Zifeng; Men, Lihui; Chen, Weijia; Liu, Zhiqiang; Liu, Zhongying

2016-05-26

Deficiency of vital energy (DE) is called Qi-deficiency, a traditional Chinese medicine syndrome. It is an indicator of a disease emerging though fuzzy, dynamic, complex, nonspecific and subjective. Ginseng is regarded as the king of herbs. It is famous for the function of replenishing qi in traditional Chinese medicine. It has treatment potential for DE caused by various reasons. This study aimed to investigate the mechanism of ginseng treating symptom DE with the method of metabolomics. Thirty-five rats were randomly divided into three groups: normal control group, DE model group and ginseng treatment group. The DE model rats were administered daily with ginseng decoctiondecoctiondecoction intragastrically and others with water for 15 days. Urine was analyzed with ultra performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS). Principal component analysis (PCA) and orthogonal projection to latent structures squares-discriminant analysis (OPLS-DA) were built to distinguish the three groups in this study and find potential biomarkers. The three groups are clearly separated and find out their metabolic distinction in PCA score plots. It showed that the metabolic profile of ginseng treatment group was changed to normal control group after administration of ginseng. Fifteen potential biomarkers are identified by OPLS-DA including Xanthurenic acid, kynurenic acid, Pantothenic acid, which are chiefly involved in tryptophan metabolism, taurine and hypotaurine metabolism, citric acid cycle, bile acid biosynthesis, alpha linolenic acid and linoleic acid metabolism. These biomarkers and the networks of their corresponding pathways will help to explain the mechanism of DE and ginseng treatment. The results of blood biochemical indicators routine and urinary metabonomic reveal that ginseng have good abilities to regulate the energy metabolism, immune function and antioxidant activities. And UPLC-Q-TOF-MS-based metabolomics can provide useful information for the understanding of metabolic changes in DE rats after administration of ginseng in urine. The biomarkers and their corresponding pathways will provide further information of the mechanisms of ginseng in treating DE. This work also proves that the method of metabonomics is effective in traditional Chinese medicinal research. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Autologous Doping with Cryopreserved Red Blood Cells – Effects on Physical Performance and Detection by Multivariate Statistics

PubMed Central

Malm, Christer B.; Khoo, Nelson S.; Granlund, Irene; Lindstedt, Emilia; Hult, Andreas

2016-01-01

The discovery of erythropoietin (EPO) simplified blood doping in sports, but improved detection methods, for EPO has forced cheating athletes to return to blood transfusion. Autologous blood transfusion with cryopreserved red blood cells (RBCs) is the method of choice, because no valid method exists to accurately detect such event. In endurance sports, it can be estimated that elite athletes improve performance by up to 3% with blood doping, regardless of method. Valid detection methods for autologous blood doping is important to maintain credibility of athletic performances. Recreational male (N = 27) and female (N = 11) athletes served as Transfusion (N = 28) and Control (N = 10) subjects in two different transfusion settings. Hematological variables and physical performance were measured before donation of 450 or 900 mL whole blood, and until four weeks after re-infusion of the cryopreserved RBC fraction. Blood was analyzed for transferrin, iron, Hb, EVF, MCV, MCHC, reticulocytes, leucocytes and EPO. Repeated measures multivariate analysis of variance (MANOVA) and pattern recognition using Principal Component Analysis (PCA) and Orthogonal Projections of Latent Structures (OPLS) discriminant analysis (DA) investigated differences between Control and Transfusion groups over time. Significant increase in performance (15 ± 8%) and VO2max (17 ± 10%) (mean ± SD) could be measured 48 h after RBC re-infusion, and remained increased for up to four weeks in some subjects. In total, 533 blood samples were included in the study (Clean = 220, Transfused = 313). In response to blood transfusion, the largest change in hematological variables occurred 48 h after blood donation, when Control and Transfused groups could be separated with OPLS-DA (R2 = 0.76/Q2 = 0.59). RBC re-infusion resulted in the best model (R2 = 0.40/Q2 = 0.10) at the first sampling point (48 h), predicting one false positive and one false negative. Over all, a 25% and 86% false positives ratio was achieved in two separate trials. In conclusions, autologous re-infusion of RBCs increased VO2max and performance as hypothesized, but hematological profiling by multivariate statistics could not reach the WADA stipulated false positive ratio of <0.001% at any time point investigated. A majority of samples remained within limits of normal individual variation at all times. PMID:27284981

The validity of the potential model in predicting the structural, dynamical, thermodynamic properties of the unary and binary mixture of water-alcohol: Methanol-water case

NASA Astrophysics Data System (ADS)

Obeidat, Abdalla; Abu-Ghazleh, Hind

2018-06-01

Two intermolecular potential models of methanol (TraPPE-UA and OPLS-AA) have been used in order to examine their validity in reproducing the selected structural, dynamical, and thermodynamic properties in the unary and binary systems. These two models are combined with two water models (SPC/E and TIP4P). The temperature dependence of density, surface tension, diffusion and structural properties for the unary system has been computed over specific range of temperatures (200-300K). The very good performance of the TraPPE-UA potential model in predicting surface tension, diffusion, structure, and density of the unary system led us to examine its accuracy and performance in its aqueous solution. In the binary system the same properties were examined, using different mole fractions of methanol. The TraPPE-UA model combined with TIP4P-water shows a very good agreement with the experimental results for density and surface tension properties; whereas the OPLS-AA combined with SPCE-water shows a very agreement with experimental results regarding the diffusion coefficients. Two different approaches have been used in calculating the diffusion coefficient in the mixture, namely the Einstein equation (EE) and Green-Kubo (GK) method. Our results show the advantageous of applying GK over EE in reproducing the experimental results and in saving computer time.

Conformational analysis of bis(methylthio)methane and diethyl sulfide molecules in the liquid phase: reverse Monte Carlo studies using classical interatomic potential functions.

PubMed

Gereben, Orsolya; Pusztai, László

2013-11-13

Series of flexible molecule reverse Monte Carlo calculations, using bonding and non-bonding interatomic potential functions (FMP-RMC), were performed starting from previous molecular dynamics results that had applied the OPLS-AA and EncadS force fields. During RMC modeling, the experimental x-ray total scattering structure factor was approached. The discrepancy between experimental and calculated structure factors, in comparison with the molecular dynamics results, decreased substantially in each case. The room temperature liquid structure of bis(methylthio)methane is excellently described by the FMP-RMC simulation that applied the EncadS force field parameters. The main conformer was found to be AG with 55.2%, followed by 37.2% of G(+)G(+) (G(-)G(-)) and 7.6% of AA; the stability of the G(+)G(+) (G(-)G(-)) conformer is most probably caused by the anomer effect. The liquid structure of diethyl sulfide can be best described by applying the OPLS-AA force field parameters during FMP-RMC simulation, although in this case the force field parameters were found to be not fully compatible with experimental data. Here, the two main conformers are AG (50.6%) and the AA (40%). In addition to findings on the actual real systems, a fairly detailed comparison between traditional and FMP-RMC methodology is provided.

Is the Conformational Ensemble of Alzheimer’s Aβ10-40 Peptide Force Field Dependent?

PubMed Central

Siwy, Christopher M.

2017-01-01

By applying REMD simulations we have performed comparative analysis of the conformational ensembles of amino-truncated Aβ10-40 peptide produced with five force fields, which combine four protein parameterizations (CHARMM36, CHARMM22*, CHARMM22/cmap, and OPLS-AA) and two water models (standard and modified TIP3P). Aβ10-40 conformations were analyzed by computing secondary structure, backbone fluctuations, tertiary interactions, and radius of gyration. We have also calculated Aβ10-40 3JHNHα-coupling and RDC constants and compared them with their experimental counterparts obtained for the full-length Aβ1-40 peptide. Our study led us to several conclusions. First, all force fields predict that Aβ adopts unfolded structure dominated by turn and random coil conformations. Second, specific TIP3P water model does not dramatically affect secondary or tertiary Aβ10-40 structure, albeit standard TIP3P model favors slightly more compact states. Third, although the secondary structures observed in CHARMM36 and CHARMM22/cmap simulations are qualitatively similar, their tertiary interactions show little consistency. Fourth, two force fields, OPLS-AA and CHARMM22* have unique features setting them apart from CHARMM36 or CHARMM22/cmap. OPLS-AA reveals moderate β-structure propensity coupled with extensive, but weak long-range tertiary interactions leading to Aβ collapsed conformations. CHARMM22* exhibits moderate helix propensity and generates multiple exceptionally stable long- and short-range interactions. Our investigation suggests that among all force fields CHARMM22* differs the most from CHARMM36. Fifth, the analysis of 3JHNHα-coupling and RDC constants based on CHARMM36 force field with standard TIP3P model led us to an unexpected finding that in silico Aβ10-40 and experimental Aβ1-40 constants are generally in better agreement than these quantities computed and measured for identical peptides, such as Aβ1-40 or Aβ1-42. This observation suggests that the differences in the conformational ensembles of Aβ10-40 and Aβ1-40 are small and the former can be used as proxy of the full-length peptide. Based on this argument, we concluded that CHARMM36 force field with standard TIP3P model produces the most accurate representation of Aβ10-40 conformational ensemble. PMID:28085875

Prediction of Mechanical Properties of Polymers With Various Force Fields

NASA Technical Reports Server (NTRS)

Odegard, Gregory M.; Clancy, Thomas C.; Gates, Thomas S.

2005-01-01

The effect of force field type on the predicted elastic properties of a polyimide is examined using a multiscale modeling technique. Molecular Dynamics simulations are used to predict the atomic structure and elastic properties of the polymer by subjecting a representative volume element of the material to bulk and shear finite deformations. The elastic properties of the polyimide are determined using three force fields: AMBER, OPLS-AA, and MM3. The predicted values of Young s modulus and shear modulus of the polyimide are compared with experimental values. The results indicate that the mechanical properties of the polyimide predicted with the OPLS-AA force field most closely matched those from experiment. The results also indicate that while the complexity of the force field does not have a significant effect on the accuracy of predicted properties, small differences in the force constants and the functional form of individual terms in the force fields determine the accuracy of the force field in predicting the elastic properties of the polyimide.

Estimating and Interpreting Latent Variable Interactions: A Tutorial for Applying the Latent Moderated Structural Equations Method

ERIC Educational Resources Information Center

Maslowsky, Julie; Jager, Justin; Hemken, Douglas

2015-01-01

Latent variables are common in psychological research. Research questions involving the interaction of two variables are likewise quite common. Methods for estimating and interpreting interactions between latent variables within a structural equation modeling framework have recently become available. The latent moderated structural equations (LMS)…

Immunotoxicity of 2,3,7,8-tetrachlorodibenzo-p-dioxin in a complex environmental mixture from the Love Canal

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

Silkworth, J.B.; Cutler, D.S.; Sack, G.

The organic phase of the leachate (OPL) from the Love Canal chemical dump site contains more than 100 organic compounds including 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD). The immunotoxic potential of OPL was determined in two mouse strains which differ in their sensitivity to aromatic hydrocarbon (Ah) receptor-mediated toxicity. OPL was administered in corn oil in a single oral gavage to male BALB/cByJ (Ahb/Ahb) mice (0.5, 0.8, or 1.1 g/kg) and DBA/2J (Ahd/Ahd) mice (0.6, 0.9, or 1.3 g/kg). TCDD was similarly administered at 0.25, 1.0, 4.0, or 16.0 micrograms/kg. Two days later all mice were immunized with sheep erythrocytes (SRBC). The antibody responsemore » (PFC) and organ weights were evaluated 4 days later. OPL produced thymic atrophy and hepatomegaly in both strains at all dose levels. The PFC/spleen in BALB/cByJ mice was significantly reduced at the three doses to 34, 13, and 15%, respectively, of the control response. Serum anti-SRBC antibody levels and relative spleen weights were also reduced. The only immune effect in the DBA/2J mice was a decrease of the PFC/spleen to 58% of the control at the highest dose. TCDD decreased the relative thymus and spleen weights only in BALB/cByJ mice. However, TCDD produced hepatomegaly, a decrease in serum antibody, and a decrease in PFC/spleen in both BALB/cByJ and DBA/2J mice to 3 and 15%, respectively, at 16 micrograms/kg. Thus, the TCDD dose required to cause a 50% suppression (ED50) of PFC/spleen for the BALB/cByJ and DBA/2J strains was 1.84 and 3.89 micrograms/kg, respectively. The ED50 for OPL was 0.24 g/kg in BALB/cByJ mice. The TCDD concentration in the OPL was estimated to be 7.6 ppm, which agrees closely with the chemical analysis (3 ppm).« less

Photo-physical properties and triplet-triplet absorption of platinum(II) acetylides in solid PMMA matrices

NASA Astrophysics Data System (ADS)

Glimsdal, Eirik; Westlund, Robert; Lindgren, Mikael

2009-05-01

Because of their strong nonlinear optical properties, Platinum(II) acetylides are investigated as potential chromophores for optical power limiting (OPL) applications. The strong excited state absorption and efficient intersystem crossing to the triplet states in these materials are desired properties for good OPL performance. We recently reported on OPL and photo-physical properties of Pt(II)-acetylide chromophores in solution, modified with thiophenyl or triazole groups. [R. Westlund et al. J. Mater. Chem. 18, 166 (2008); E. Glimsdal et al. Proc. SPIE 6740, 67400M (2007)] The chromophores were later incorporated into poly(methyl-methacrylate) (PMMA) glasses. A variety of doped organic solids were prepared, reaching concentrations of up to 13 wt% of the guest molecule. Raman spectra of the doped solid devices proved that the chemical structure of the nonlinear dyes remains intact upon the polymerization of the solid matrix. Luminescence spectra confirm that the basic photo-physical properties (absorption, emission and inter-system crossing) observed for the solute molecules in THF are maintained also in the solid state. In particular, the phosphorescence lifetime stays in the order of μs to ms, just as in the oxygen evacuated liquid samples. Also, the wavelength dependence and time-dynamics of the triplet absorption spectra of the dyes, dissolved in THF solution and dispersed in solid PMMA matrices, were investigated and compared. Ground state UV absorption spectra between 300 and 420 nm have corresponding broad band visible triplet-triplet absorption between 400 and 800 nm. The triplet state extinction coefficients were determined to be in the order of 104 M-1cm-1.

Bayesian Semiparametric Structural Equation Models with Latent Variables

ERIC Educational Resources Information Center

Yang, Mingan; Dunson, David B.

2010-01-01

Structural equation models (SEMs) with latent variables are widely useful for sparse covariance structure modeling and for inferring relationships among latent variables. Bayesian SEMs are appealing in allowing for the incorporation of prior information and in providing exact posterior distributions of unknowns, including the latent variables. In…

The Impact of Ignoring the Level of Nesting Structure in Nonparametric Multilevel Latent Class Models

ERIC Educational Resources Information Center

Park, Jungkyu; Yu, Hsiu-Ting

2016-01-01

The multilevel latent class model (MLCM) is a multilevel extension of a latent class model (LCM) that is used to analyze nested structure data structure. The nonparametric version of an MLCM assumes a discrete latent variable at a higher-level nesting structure to account for the dependency among observations nested within a higher-level unit. In…

Paternity leave experiences of NHS doctors.

PubMed

Gordon, Hannah; Szram, Joanna

2013-10-01

This study assesses NHS doctors' experiences of paternity leave and evaluates whether practices have changed since the introduction of additional paternity leave (APL) in April 2011. An anonymised online survey designed to discover experiences and uptake of APL and ordinary paternity leave (OPL) was distributed to all members of the London Deanery Synapse® network. In total, 364 fathers responded. Their seniority ranged from foundation trainees to consultants. Following the formal introduction of OPL in 2003, the number of fathers taking any paternity leave increased (from 50% to 95.6%). The majority of respondents (76.7%) felt well supported by their employer. Since the introduction of APL, 3% of respondents took additional leave. Reasons for the low uptake of APL included the impracticalities of the law, poor awareness and perceived attitudes and implications for training. Problems with OPL included the inadequate provision of cover and difficulties in timing the leave appropriately.

Realization of an omnidirectional source of sound using parametric loudspeakers.

PubMed

Sayin, Umut; Artís, Pere; Guasch, Oriol

2013-09-01

Parametric loudspeakers are often used in beam forming applications where a high directivity is required. Withal, in this paper it is proposed to use such devices to build an omnidirectional source of sound. An initial prototype, the omnidirectional parametric loudspeaker (OPL), consisting of a sphere with hundreds of ultrasonic transducers placed on it has been constructed. The OPL emits audible sound thanks to the parametric acoustic array phenomenon, and the close proximity and the large number of transducers results in the generation of a highly omnidirectional sound field. Comparisons with conventional dodecahedron loudspeakers have been made in terms of directivity, frequency response, and in applications such as the generation of diffuse acoustic fields in reverberant chambers. The OPL prototype has performed better than the conventional loudspeaker especially for frequencies higher than 500 Hz, its main drawback being the difficulty to generate intense pressure levels at low frequencies.

Toward polarizable AMOEBA thermodynamics at fixed charge efficiency using a dual force field approach: application to organic crystals.

PubMed

Nessler, Ian J; Litman, Jacob M; Schnieders, Michael J

2016-11-09

First principles prediction of the structure, thermodynamics and solubility of organic molecular crystals, which play a central role in chemical, material, pharmaceutical and engineering sciences, challenges both potential energy functions and sampling methodologies. Here we calculate absolute crystal deposition thermodynamics using a novel dual force field approach whose goal is to maintain the accuracy of advanced multipole force fields (e.g. the polarizable AMOEBA model) while performing more than 95% of the sampling in an inexpensive fixed charge (FC) force field (e.g. OPLS-AA). Absolute crystal sublimation/deposition phase transition free energies were determined using an alchemical path that grows the crystalline state from a vapor reference state based on sampling with the OPLS-AA force field, followed by dual force field thermodynamic corrections to change between FC and AMOEBA resolutions at both end states (we denote the three step path as AMOEBA/FC). Importantly, whereas the phase transition requires on the order of 200 ns of sampling per compound, only 5 ns of sampling was needed for the dual force field thermodynamic corrections to reach a mean statistical uncertainty of 0.05 kcal mol -1 . For five organic compounds, the mean unsigned error between direct use of AMOEBA and the AMOEBA/FC dual force field path was only 0.2 kcal mol -1 and not statistically significant. Compared to experimental deposition thermodynamics, the mean unsigned error for AMOEBA/FC (1.4 kcal mol -1 ) was more than a factor of two smaller than uncorrected OPLS-AA (3.2 kcal mol -1 ). Overall, the dual force field thermodynamic corrections reduced condensed phase sampling in the expensive force field by a factor of 40, and may prove useful for protein stability or binding thermodynamics in the future.

Flexible Modeling of Latent Task Structures in Multitask Learning

DTIC Science & Technology

2012-06-26

Flexible Modeling of Latent Task Structures in Multitask Learning Alexandre Passos† apassos@cs.umass.edu Computer Science Department, University of...of Maryland, College Park, MD USA Abstract Multitask learning algorithms are typically designed assuming some fixed, a priori known latent structure...shared by all the tasks. However, it is usually unclear what type of latent task structure is the most ap- propriate for a given multitask learning prob

Optically phase-locked electronic speckle pattern interferometer

NASA Astrophysics Data System (ADS)

Moran, Steven E.; Law, Robert; Craig, Peter N.; Goldberg, Warren M.

1987-02-01

The design, theory, operation, and characteristics of an optically phase-locked electronic speckle pattern interferometer (OPL-ESPI) are described. The OPL-ESPI system couples an optical phase-locked loop with an ESPI system to generate real-time equal Doppler speckle contours of moving objects from unstable sensor platforms. In addition, the optical phase-locked loop provides the basis for a new ESPI video signal processing technique which incorporates local oscillator phase shifting coupled with video sequential frame subtraction.

Phenolic Analysis and Theoretic Design for Chinese Commercial Wines' Authentication.

PubMed

Li, Si-Yu; Zhu, Bao-Qing; Reeves, Malcolm J; Duan, Chang-Qing

2018-01-01

To develop a robust tool for Chinese commercial wines' varietal, regional, and vintage authentication, phenolic compounds in 121 Chinese commercial dry red wines were detected and quantified by using high-performance liquid chromatography triple-quadrupole mass spectrometry (HPLC-QqQ-MS/MS), and differentiation abilities of principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), and orthogonal partial least squares discriminant analysis (OPLS-DA) were compared. Better than PCA and PLS-DA, OPLS-DA models used to differentiate wines according to their varieties (Cabernet Sauvignon or other varieties), regions (east or west Cabernet Sauvignon wines), and vintages (young or old Cabernet Sauvignon wines) were ideally established. The S-plot provided in OPLS-DA models showed the key phenolic compounds which were both statistically and biochemically significant in sample differentiation. Besides, the potential of the OPLS-DA models in deeper sample differentiating of more detailed regional and vintage information of wines was proved optimistic. On the basis of our results, a promising theoretic design for wine authentication was further proposed for the first time, which might be helpful in practical authentication of more commercial wines. The phenolic data of 121 Chinese commercial dry red wines was processed with different statistical tools for varietal, regional, and vintage differentiation. A promising theoretical design was summarized, which might be helpful for wine authentication in practical situation. © 2017 Institute of Food Technologists®.

Cell volume and plasma membrane osmotic water permeability in epithelial cell layers measured by interferometry.

PubMed

Farinas, J; Verkman, A S

1996-12-01

The development of strategies to measure plasma membrane osmotic water permeability (Pf) in epithelial cells has been motivated by the identification of a family of molecular water channels. A general approach utilizing interferometry to measure cell shape and volume was developed and applied to measure Pf in cell layers. The method is based on the cell volume dependence of optical path length (OPL) for a light beam passing through the cell. The small changes in OPL were measured by interferometry. A mathematical model was developed to relate the interference signal to cell volume changes for cells of arbitrary shape and size. To validate the model, a Mach-Zehnder interference microscope was used to image OPL in an Madin Darby Canine Kidney (MDCK) cell layer and to reconstruct the three-dimensional cell shape (OPL resolution < lambda/25). As predicted by the model, a doubling of cell volume resulted in a change in OPL that was proportional to the difference in refractive indices between water and the extracellular medium. The time course of relative cell volume in response to an osmotic gradient was computed from serial interference images. To measure cell volume without microscopy and image analysis, a Mach-Zehnder interferometer was constructed in which one of two interfering laser beams passed through a flow chamber containing the cell layer. The interference signal in response to an osmotic gradient was analyzed to quantify the time course of relative cell volume. The calculated MDCK cell plasma membrane Pf of 6.1 x 10(-4) cm/s at 24 degrees C agreed with that obtained by interference microscopy and by a total internal reflection fluorescence method. Interferometry was also applied to measure the apical plasma membrane water permeability of intact toad urinary bladder; Pf increased fivefold after forskolin stimulation to 0.04 cm/s at 23 degrees C. These results establish and validate the application of interferometry to quantify cell volume and osmotic water permeability in cell layers.

Testing Specific Hypotheses Concerning Latent Group Differences in Multi-group Covariance Structure Analysis with Structured Means.

ERIC Educational Resources Information Center

Dolan, Conor V.; Molenaar, Peter C. M.

1994-01-01

In multigroup covariance structure analysis with structured means, the traditional latent selection model is formulated as a special case of phenotypic selection. Illustrations with real and simulated data demonstrate how one can test specific hypotheses concerning selection on latent variables. (SLD)

Volatiles and primary metabolites profiling in two Hibiscus sabdariffa (roselle) cultivars via headspace SPME-GC-MS and chemometrics.

PubMed

Farag, Mohamed A; Rasheed, Dalia M; Kamal, Islam M

2015-12-01

Hibiscus sabdariffa (roselle) is a plant of considerable commercial importance worldwide as functional food due to its organic acids, mucilage, anthocyanins, macro and micro-nutrients content. Although Hibiscus flowers are emerging as very competitive targets for phytochemical studies, very little is known about their volatile composition and or aroma, such knowledge can be suspected to be relevant for understanding its olfactory and taste properties. To provide insight into Hibiscus flower aroma composition and for its future use in food and or pharmaceutical industry, volatile constituents from 2 cultivars grown in Egypt, viz. Aswan and Sudan-1 were profiled using solid-phase microextraction (SPME) coupled to GCMS. A total of 104 volatiles were identified with sugar and fatty acid derived volatiles amounting for the major volatile classes. To reveal for cultivar effect on volatile composition in an untargeted manner, multivariate data analysis was applied. Orthogonal projection to latent structures-discriminant analysis (OPLS-DA) revealed for 1-octen-3-ol versus furfural/acetic acid enrichment in Aswan and Sudan-1 cvs., respectively. Primary metabolites contributing to roselle taste and nutritional value viz. sugars and organic acids were profiled using GC-MS after silylation. The impact of probiotic bacteria on roselle infusion aroma profile was further assessed and revealed for the increase in furfural production with Lactobacillus plantarum inoculation and without affecting its anthocyanin content. This study provides the most complete map for volatiles, sugars and organic acids distribution in two Hibiscus flower cultivars and its fermented product. Copyright © 2015 Elsevier Ltd. All rights reserved.

Gas chromatography/mass spectrometry based component profiling and quality prediction for Japanese sake.

PubMed

Mimura, Natsuki; Isogai, Atsuko; Iwashita, Kazuhiro; Bamba, Takeshi; Fukusaki, Eiichiro

2014-10-01

Sake is a Japanese traditional alcoholic beverage, which is produced by simultaneous saccharification and alcohol fermentation of polished and steamed rice by Aspergillus oryzae and Saccharomyces cerevisiae. About 300 compounds have been identified in sake, and the contribution of individual components to the sake flavor has been examined at the same time. However, only a few compounds could explain the characteristics alone and most of the attributes still remain unclear. The purpose of this study was to examine the relationship between the component profile and the attributes of sake. Gas chromatography coupled with mass spectrometry (GC/MS)-based non-targeted analysis was employed to obtain the low molecular weight component profile of Japanese sake including both nonvolatile and volatile compounds. Sake attributes and overall quality were assessed by analytical descriptive sensory test and the prediction model of the sensory score from the component profile was constructed by means of orthogonal projections to latent structures (OPLS) regression analysis. Our results showed that 12 sake attributes [ginjo-ka (aroma of premium ginjo sake), grassy/aldehydic odor, sweet aroma/caramel/burnt odor, sulfury odor, sour taste, umami, bitter taste, body, amakara (dryness), aftertaste, pungent/smoothness and appearance] and overall quality were accurately explained by component profiles. In addition, we were able to select statistically significant components according to variable importance on projection (VIP). Our methodology clarified the correlation between sake attribute and 200 low molecular components and presented the importance of each component thus, providing new insights to the flavor study of sake. Copyright © 2014 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.

Metabolomics study of human urinary metabolome modifications after intake of almond (Prunus dulcis (Mill.) D.A. Webb) skin polyphenols.

PubMed

Llorach, Rafael; Garrido, Ignacio; Monagas, Maria; Urpi-Sarda, Mireia; Tulipani, Sara; Bartolome, Begona; Andres-Lacueva, Cristina

2010-11-05

Almond, as a part of the nut family, is an important source of biological compounds, and specifically, almond skins have been considered an important source of polyphenols, including flavan-3-ols and flavonols. Polyphenol metabolism may produce several classes of metabolites that could often be more biologically active than their dietary precursor and could also become a robust new biomarker of almond polyphenol intake. In order to study urinary metabolome modifications during the 24 h after a single dose of almond skin extract, 24 volunteers (n = 24), who followed a polyphenol-free diet for 48 h before and during the study, ingested a dietary supplement of almond skin phenolic compounds (n = 12) or a placebo (n = 12). Urine samples were collected before ((-2)-0 h) and after (0-2 h, 2-6 h, 6-10 h, and 10-24 h) the intake and were analyzed by liquid chromatography-mass spectrometry (LC-q-TOF) and multivariate statistical analysis (principal component analysis (PCA) and orthogonal projection to latent structures (OPLS)). Putative identification of relevant biomarkers revealed a total of 34 metabolites associated with the single dose of almond extract, including host and, in particular, microbiota metabolites. As far as we know, this is the first time that conjugates of hydroxyphenylvaleric, hydroxyphenylpropionic, and hydroxyphenylacetic acids have been identified in human samples after the consumption of flavan-3-ols through a metabolomic approach. The results showed that this non-targeted approach could provide new intake biomarkers, contributing to the development of the food metabolome as an important part of the human urinary metabolome.

On the optical path length in refracting media

NASA Astrophysics Data System (ADS)

Hasbun, Javier E.

2018-04-01

The path light follows as it travels through a substance depends on the substance's index of refraction. This path is commonly known as the optical path length (OPL). In geometrical optics, the laws of reflection and refraction are simple examples for understanding the path of light travel from source to detector for constant values of the traveled substances' refraction indices. In more complicated situations, the Euler equation can be quite useful and quite important in optics courses. Here, the well-known Euler differential equation (EDE) is used to obtain the OPL for several index of refraction models. For pedagogical completeness, the OPL is also obtained through a modified Monte Carlo (MC) method, versus which the various results obtained through the EDE are compared. The examples developed should be important in projects involving undergraduate as well as graduate students in an introductory optics course. A simple matlab script (program) is included that can be modified by students who wish to pursue the subject further.

Chemical images of marine bio-active compounds by surface enhanced Raman spectroscopy and transposed orthogonal partial least squares (T-OPLS).

PubMed

Abbas, Aamer; Josefson, Mats; Nylund, Göran M; Pavia, Henrik; Abrahamsson, Katarina

2012-08-06

Surface enhanced Raman spectroscopy combined with transposed Orthogonal Partial Least Squares (T-OPLS) was shown to produce chemical images of the natural antibacterial surface-active compound 1,1,3,3-tetrabromo-2-heptanone (TBH) on Bonnemaisonia hamifera. The use of gold colloids functionalised with the internal standard 4-mercapto-benzonitrile (MBN) made it possible to create images of the relative concentration of TBH over the surfaces. A gradient of TBH could be mapped over and in the close vicinity of the B. hamifera algal vesicles at the attomol/pixel level. T-OPLS produced a measure of the spectral correlation for each pixel of the hyperspectral images whilst not including spectral variation that was linearly independent of the target spectrum. In this paper we show the possibility to retrieve specific spectral information with a low magnitude in a complex matrix. Copyright © 2012 Elsevier B.V. All rights reserved.

Latent Structure of Motor Abilities in Pre-School Children

ERIC Educational Resources Information Center

Vatroslav, Horvat

2011-01-01

The theoretical and practical knowledge which have so far been acquired through work with pre-school children pointed to the conclusion that the structures of the latent dimensions of the motor abilities differ greatly from such a structure, in pre-school children and adults alike. Establishing the latent structure of the motor abilities in…

Digital-holographic analysis of femtosecond laser-induced photodisruption in ocular tissue

NASA Astrophysics Data System (ADS)

Saerchen, Emanuel; Biessy, Kevin; Kemper, Björn; Lubatschowski, Holger

2014-02-01

High repetition rated femtosecond laser oscillator systems with low pulse energy are more often applied for precise and safer eye surgery. Especially, the cutting procedure in the crystalline lens is of high important for presbyopia treatment. Nevertheless, the fundamental laser tissue interaction process is not completely understood, because apparently a self-induced process takes place, were one modified region changes the focusing behavior of following laser pulses. We used a MHz repetition rate femtosecond laser system with nJ-pulse energy which were focused inside an ocular-tissue-phantom (Hydroxy-ethylmethacrylat - HEMA) to induce photodisruption. The material change, caused by the fs-pulses was measured simultaneously with a compact digital-holographic microscope. To investigate the material manipulation at different time scales, we used a continuously illuminating light source. The holographic images provide quantitative values for optical path length difference (OPL), which is equivalent to a refractive index change. This change of the optical properties may cause following pulses to obtain different focusing conditions. Time lapse measurements during the laser application were performed, which show the temporal evolution of OPL. An increase of OPL during the laser application was measured, which was followed by a decrease in OPL after laser processing. Furthermore, similar experiments were performed in distilled water and in native porcine crystalline lenses. The fs-laser cutting effects in HEMA and crystalline lens were transferable. Simultaneous measurements of the material modification during the cutting process give rise to better knowledge of treatment modalities during ocular tissue processing.

The Integration of Continuous and Discrete Latent Variable Models: Potential Problems and Promising Opportunities

ERIC Educational Resources Information Center

Bauer, Daniel J.; Curran, Patrick J.

2004-01-01

Structural equation mixture modeling (SEMM) integrates continuous and discrete latent variable models. Drawing on prior research on the relationships between continuous and discrete latent variable models, the authors identify 3 conditions that may lead to the estimation of spurious latent classes in SEMM: misspecification of the structural model,…

Using SAS PROC CALIS to fit Level-1 error covariance structures of latent growth models.

PubMed

Ding, Cherng G; Jane, Ten-Der

2012-09-01

In the present article, we demonstrates the use of SAS PROC CALIS to fit various types of Level-1 error covariance structures of latent growth models (LGM). Advantages of the SEM approach, on which PROC CALIS is based, include the capabilities of modeling the change over time for latent constructs, measured by multiple indicators; embedding LGM into a larger latent variable model; incorporating measurement models for latent predictors; and better assessing model fit and the flexibility in specifying error covariance structures. The strength of PROC CALIS is always accompanied with technical coding work, which needs to be specifically addressed. We provide a tutorial on the SAS syntax for modeling the growth of a manifest variable and the growth of a latent construct, focusing the documentation on the specification of Level-1 error covariance structures. Illustrations are conducted with the data generated from two given latent growth models. The coding provided is helpful when the growth model has been well determined and the Level-1 error covariance structure is to be identified.

Detecting Mixtures from Structural Model Differences Using Latent Variable Mixture Modeling: A Comparison of Relative Model Fit Statistics

ERIC Educational Resources Information Center

Henson, James M.; Reise, Steven P.; Kim, Kevin H.

2007-01-01

The accuracy of structural model parameter estimates in latent variable mixture modeling was explored with a 3 (sample size) [times] 3 (exogenous latent mean difference) [times] 3 (endogenous latent mean difference) [times] 3 (correlation between factors) [times] 3 (mixture proportions) factorial design. In addition, the efficacy of several…

Mixture IRT Model with a Higher-Order Structure for Latent Traits

ERIC Educational Resources Information Center

Huang, Hung-Yu

2017-01-01

Mixture item response theory (IRT) models have been suggested as an efficient method of detecting the different response patterns derived from latent classes when developing a test. In testing situations, multiple latent traits measured by a battery of tests can exhibit a higher-order structure, and mixtures of latent classes may occur on…

Bayesian latent structure modeling of walking behavior in a physical activity intervention

PubMed Central

Lawson, Andrew B; Ellerbe, Caitlyn; Carroll, Rachel; Alia, Kassandra; Coulon, Sandra; Wilson, Dawn K; VanHorn, M Lee; St George, Sara M

2017-01-01

The analysis of walking behavior in a physical activity intervention is considered. A Bayesian latent structure modeling approach is proposed whereby the ability and willingness of participants is modeled via latent effects. The dropout process is jointly modeled via a linked survival model. Computational issues are addressed via posterior sampling and a simulated evaluation of the longitudinal model’s ability to recover latent structure and predictor effects is considered. We evaluate the effect of a variety of socio-psychological and spatial neighborhood predictors on the propensity to walk and the estimation of latent ability and willingness in the full study. PMID:24741000

Cell volume and plasma membrane osmotic water permeability in epithelial cell layers measured by interferometry.

PubMed Central

Farinas, J; Verkman, A S

1996-01-01

The development of strategies to measure plasma membrane osmotic water permeability (Pf) in epithelial cells has been motivated by the identification of a family of molecular water channels. A general approach utilizing interferometry to measure cell shape and volume was developed and applied to measure Pf in cell layers. The method is based on the cell volume dependence of optical path length (OPL) for a light beam passing through the cell. The small changes in OPL were measured by interferometry. A mathematical model was developed to relate the interference signal to cell volume changes for cells of arbitrary shape and size. To validate the model, a Mach-Zehnder interference microscope was used to image OPL in an Madin Darby Canine Kidney (MDCK) cell layer and to reconstruct the three-dimensional cell shape (OPL resolution < lambda/25). As predicted by the model, a doubling of cell volume resulted in a change in OPL that was proportional to the difference in refractive indices between water and the extracellular medium. The time course of relative cell volume in response to an osmotic gradient was computed from serial interference images. To measure cell volume without microscopy and image analysis, a Mach-Zehnder interferometer was constructed in which one of two interfering laser beams passed through a flow chamber containing the cell layer. The interference signal in response to an osmotic gradient was analyzed to quantify the time course of relative cell volume. The calculated MDCK cell plasma membrane Pf of 6.1 x 10(-4) cm/s at 24 degrees C agreed with that obtained by interference microscopy and by a total internal reflection fluorescence method. Interferometry was also applied to measure the apical plasma membrane water permeability of intact toad urinary bladder; Pf increased fivefold after forskolin stimulation to 0.04 cm/s at 23 degrees C. These results establish and validate the application of interferometry to quantify cell volume and osmotic water permeability in cell layers. Images FIGURE 1 FIGURE 2 FIGURE 3 FIGURE 4 FIGURE 6 PMID:8968620

Evidence for the Continuous Latent Structure of Mania in the Epidemiologic Catchment Area from Multiple Latent Structure and Construct Validation Methodologies

PubMed Central

Prisciandaro, James J.; Roberts, John E.

2011-01-01

Background Although psychiatric diagnostic systems have conceptualized mania as a discrete phenomenon, appropriate latent structure investigations testing this conceptualization are lacking. In contrast to these diagnostic systems, several influential theories of mania have suggested a continuous conceptualization. The present study examined whether mania has a continuous or discrete latent structure using a comprehensive approach including taxometric, information-theoretic latent distribution modeling (ITLDM), and predictive validity methodologies in the Epidemiologic Catchment Area (ECA) study. Methods Eight dichotomous manic symptom items were submitted to a variety of latent structural analyses; including factor analyses, taxometric procedures, and ITLDM; in 10,105 ECA community participants. Additionally, a variety of continuous and discrete models of mania were compared in terms of their relative abilities to predict outcomes (i.e., health service utilization, internalizing and externalizing disorders, and suicidal behavior). Results Taxometric and ITLDM analyses consistently supported a continuous conceptualization of mania. In ITLDM analyses, a continuous model of mania demonstrated 6:52:1 odds over the best fitting latent class model of mania. Factor analyses suggested that the continuous structure of mania was best represented by a single latent factor. Predictive validity analyses demonstrated a consistent superior ability of continuous models of mania relative to discrete models. Conclusions The present study provided three independent lines of support for a continuous conceptualization of mania. The implications of a continuous model of mania are discussed. PMID:20507671

The Latent Structure of Dietary Restraint, Body Dissatisfaction, and Drive for Thinness: A Series of Taxometric Analyses

ERIC Educational Resources Information Center

Holm-Denoma, Jill M.; Richey, J. Anthony; Joiner, Thomas E., Jr.

2010-01-01

Although the latent structure of various eating disorders has been explored in previous studies, no published studies have examined the latent structure of theoretically relevant variables that have been shown to cut across eating disorder diagnoses. The current study examined 3 such variables (dietary restraint, body dissatisfaction, and drive…

A Taxonomy of Latent Structure Assumptions for Probability Matrix Decomposition Models.

ERIC Educational Resources Information Center

Meulders, Michel; De Boeck, Paul; Van Mechelen, Iven

2003-01-01

Proposed a taxonomy of latent structure assumptions for probability matrix decomposition (PMD) that includes the original PMD model and a three-way extension of the multiple classification latent class model. Simulation study results show the usefulness of the taxonomy. (SLD)

A Comparison of Quantum and Molecular Mechanical Methods to Estimate Strain Energy in Druglike Fragments.

PubMed

Sellers, Benjamin D; James, Natalie C; Gobbi, Alberto

2017-06-26

Reducing internal strain energy in small molecules is critical for designing potent drugs. Quantum mechanical (QM) and molecular mechanical (MM) methods are often used to estimate these energies. In an effort to determine which methods offer an optimal balance in accuracy and performance, we have carried out torsion scan analyses on 62 fragments. We compared nine QM and four MM methods to reference energies calculated at a higher level of theory: CCSD(T)/CBS single point energies (coupled cluster with single, double, and perturbative triple excitations at the complete basis set limit) calculated on optimized geometries using MP2/6-311+G**. The results show that both the more recent MP2.X perturbation method as well as MP2/CBS perform quite well. In addition, combining a Hartree-Fock geometry optimization with a MP2/CBS single point energy calculation offers a fast and accurate compromise when dispersion is not a key energy component. Among MM methods, the OPLS3 force field accurately reproduces CCSD(T)/CBS torsion energies on more test cases than the MMFF94s or Amber12:EHT force fields, which struggle with aryl-amide and aryl-aryl torsions. Using experimental conformations from the Cambridge Structural Database, we highlight three example structures for which OPLS3 significantly overestimates the strain. The energies and conformations presented should enable scientists to estimate the expected error for the methods described and we hope will spur further research into QM and MM methods.

A quality by design approach to investigate the effect of mannitol and dicalcium phosphate qualities on roll compaction.

PubMed

Souihi, Nabil; Dumarey, Melanie; Wikström, Håkan; Tajarobi, Pirjo; Fransson, Magnus; Svensson, Olof; Josefson, Mats; Trygg, Johan

2013-04-15

Roll compaction is a continuous process for solid dosage form manufacturing increasingly popular within pharmaceutical industry. Although roll compaction has become an established technique for dry granulation, the influence of material properties is still not fully understood. In this study, a quality by design (QbD) approach was utilized, not only to understand the influence of different qualities of mannitol and dicalcium phosphate (DCP), but also to predict critical quality attributes of the drug product based solely on the material properties of that filler. By describing each filler quality in terms of several representative physical properties, orthogonal projections to latent structures (OPLS) was used to understand and predict how those properties affected drug product intermediates as well as critical quality attributes of the final drug product. These models were then validated by predicting product attributes for filler qualities not used in the model construction. The results of this study confirmed that the tensile strength reduction, known to affect plastic materials when roll compacted, is not prominent when using brittle materials. Some qualities of these fillers actually demonstrated improved compactability following roll compaction. While direct compression qualities are frequently used for roll compacted drug products because of their excellent flowability and good compaction properties, this study revealed that granules from these qualities were more poor flowing than the corresponding powder blends, which was not seen for granules from traditional qualities. The QbD approach used in this study could be extended beyond fillers. Thus any new compound/ingredient would first be characterized and then suitable formulation characteristics could be determined in silico, without running any additional experiments. Copyright © 2013 Elsevier B.V. All rights reserved.

Metabolite profiling in Trigonella seeds via UPLC-MS and GC-MS analyzed using multivariate data analyses.

PubMed

Farag, Mohamed A; Rasheed, Dalia M; Kropf, Matthias; Heiss, Andreas G

2016-11-01

Trigonella foenum-graecum is a plant of considerable value for its nutritive composition as well as medicinal effects. This study aims to examine Trigonella seeds using a metabolome-based ultra-performance liquid chromatography-mass spectrometry (UPLC-MS) in parallel to gas chromatography-mass spectrometry (GC-MS) coupled with multivariate data analyses. The metabolomic differences of seeds derived from three Trigonella species, i.e., T. caerulea, T. corniculata, and T. foenum-graecum, were assessed. Under specified conditions, we were able to identify 93 metabolites including 5 peptides, 2 phenolic acids, 22 C/O-flavonoid conjugates, 26 saponins, and 9 fatty acids using UPLC-MS. Several novel dipeptides, saponins, and flavonoids were found in Trigonella herein for the first time. Samples were classified via unsupervised principal component analysis (PCA) followed by supervised orthogonal projection to latent structures-discriminant analysis (OPLS-DA). A distinct separation among the investigated Trigonella species was revealed, with T. foenum-graecum samples found most enriched in apigenin-C-glycosides, viz. vicenins 1/3 and 2, compared to the other two species. In contrast to UPLC-MS, GC-MS was less efficient to classify specimens, with differences among specimens mostly attributed to fatty acyl esters. GC-MS analysis of Trigonella seed extracts led to the identification of 91 metabolites belonging mostly to fatty acyl esters, free fatty acids followed by organic acids, sugars, and amino acids. This study presents the first report on primary and secondary metabolite compositional differences among Trigonella seeds via a metabolomics approach and reveals that, among the species examined, the official T. foenum-graecum presents a better source of Trigonella secondary bioactive metabolites.

NMR-based Metabolomics Analysis of Liver from C57BL/6 Mouse Exposed to Ionizing Radiation

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

Xiao, Xiongjie; Hu, Mary; Zhang, Xu

The health effects of exposing to ionizing radiation are attracting great interest in the space exploration community and patients considering radiotherapy. However, the impact to metabolism after exposure to high dose radiation has not yet been clearly defined in livers. In the present study, 1H nuclear magnetic resonance (NMR) based metabolomics combined with multivariate data analysis are applied to study the changes of metabolism in the liver of C57BL/6 mouse after whole body exposure to either gamma (3.0 and 7.8 Gy) or proton (3.0 Gy) radiation. Principal component analysis (PCA) and orthogonal projection to latent structures analysis (OPLS) are employedmore » for classification and identification of potential biomarkers associated with gamma and proton irradiation. The results show that the radiation exposed groups can be well separated from the control group. At the same radiation dosage, the group exposed to proton radiation is well separated from the group exposed to gamma radiation, indicating different radiation sources induce different alterations based on metabolic profiling. Common to both gamma and proton radiation at the high radiation doses studied in this work, compared with the control groups the concentrations of choline, O-phosphocholine and trimethylamine N-oxide are decreased statistically, while those of glutamine, glutathione, malate, creatinine, phosphate, betaine and 4-hydroxyphenylacetate are statistically and significantly elevated after exposure to radiation. Since these altered metabolites are associated with multiple biological pathways, the changes suggest that the exposure to radiation induce abnormality in multiple biological pathways. In particular, metabolites such as 4-hydroxyphenylacetate, betaine, glutamine, choline and trimethylamine N-oxide may be good candidates of pre-diagnose biomarkers for ionizing radiation in liver.« less

Soft Corals Biodiversity in the Egyptian Red Sea: A Comparative MS and NMR Metabolomics Approach of Wild and Aquarium Grown Species.

PubMed

Farag, Mohamed A; Porzel, Andrea; Al-Hammady, Montasser A; Hegazy, Mohamed-Elamir F; Meyer, Achim; Mohamed, Tarik A; Westphal, Hildegard; Wessjohann, Ludger A

2016-04-01

Marine life has developed unique metabolic and physiologic capabilities and advanced symbiotic relationships to survive in the varied and complex marine ecosystems. Herein, metabolite composition of the soft coral genus Sarcophyton was profiled with respect to its species and different habitats along the coastal Egyptian Red Sea via (1)H NMR and ultra performance liquid chromatography-mass spectrometry (UPLC-MS) large-scale metabolomics analyses. The current study extends the application of comparative secondary metabolite profiling from plants to corals revealing for metabolite compositional differences among its species via a comparative MS and NMR approach. This was applied for the first time to investigate the metabolism of 16 Sarcophyton species in the context of their genetic diversity or growth habitat. Under optimized conditions, we were able to simultaneously identify 120 metabolites including 65 diterpenes, 8 sesquiterpenes, 18 sterols, and 15 oxylipids. Principal component analysis (PCA) and orthogonal projection to latent structures-discriminant analysis (OPLS) were used to define both similarities and differences among samples. For a compound based classification of coral species, UPLC-MS was found to be more effective than NMR. The main differentiations emanate from cembranoids and oxylipids. The specific metabolites that contribute to discrimination between soft corals of S. ehrenbergi from the three different growing habitats also belonged to cembrane type diterpenes, with aquarium S. ehrenbergi corals being less enriched in cembranoids compared to sea corals. PCA using either NMR or UPLC-MS data sets was found equally effective in predicting the species origin of unknown Sarcophyton. Cyclopropane containing sterols observed in abundance in corals may act as cellular membrane protectant against the action of coral toxins, that is, cembranoids.

Metabolomic and Lipidomic Analysis of Serum Samples following Curcuma longa Extract Supplementation in High-Fructose and Saturated Fat Fed Rats.

PubMed

Tranchida, Fabrice; Shintu, Laetitia; Rakotoniaina, Zo; Tchiakpe, Léopold; Deyris, Valérie; Hiol, Abel; Caldarelli, Stefano

2015-01-01

We explored, using nuclear magnetic resonance (NMR) metabolomics and fatty acids profiling, the effects of a common nutritional complement, Curcuma longa, at a nutritionally relevant dose with human use, administered in conjunction with an unbalanced diet. Indeed, traditional food supplements have been long used to counter metabolic impairments induced by unbalanced diets. Here, rats were fed either a standard diet, a high level of fructose and saturated fatty acid (HFS) diet, a diet common to western countries and that certainly contributes to the epidemic of insulin resistance (IR) syndrome, or a HFS diet with a Curcuma longa extract (1% of curcuminoids in the extract) for ten weeks. Orthogonal projections to latent structures discriminant analysis (OPLS-DA) on the serum NMR profiles and fatty acid composition (determined by GC/MS) showed a clear discrimination between HFS groups and controls. This discrimination involved metabolites such as glucose, amino acids, pyruvate, creatine, phosphocholine/glycerophosphocholine, ketone bodies and glycoproteins as well as an increase of monounsaturated fatty acids (MUFAs) and a decrease of n-6 and n-3 polyunsaturated fatty acids (PUFAs). Although the administration of Curcuma longa did not prevent the observed increase of glucose, triglycerides, cholesterol and insulin levels, discriminating metabolites were observed between groups fed HFS alone or with addition of a Curcuma longa extract, namely some MUFA and n-3 PUFA, glycoproteins, glutamine, and methanol, suggesting that curcuminoids may act respectively on the fatty acid metabolism, the hexosamine biosynthesis pathway and alcohol oxidation. Curcuma longa extract supplementation appears to be beneficial in these metabolic pathways in rats. This metabolomic approach highlights important serum metabolites that could help in understanding further the metabolic mechanisms leading to IR.

Metabolomic and Lipidomic Analysis of Serum Samples following Curcuma longa Extract Supplementation in High-Fructose and Saturated Fat Fed Rats

PubMed Central

Tranchida, Fabrice; Shintu, Laetitia; Rakotoniaina, Zo; Tchiakpe, Léopold; Deyris, Valérie; Hiol, Abel; Caldarelli, Stefano

2015-01-01

We explored, using nuclear magnetic resonance (NMR) metabolomics and fatty acids profiling, the effects of a common nutritional complement, Curcuma longa, at a nutritionally relevant dose with human use, administered in conjunction with an unbalanced diet. Indeed, traditional food supplements have been long used to counter metabolic impairments induced by unbalanced diets. Here, rats were fed either a standard diet, a high level of fructose and saturated fatty acid (HFS) diet, a diet common to western countries and that certainly contributes to the epidemic of insulin resistance (IR) syndrome, or a HFS diet with a Curcuma longa extract (1% of curcuminoids in the extract) for ten weeks. Orthogonal projections to latent structures discriminant analysis (OPLS-DA) on the serum NMR profiles and fatty acid composition (determined by GC/MS) showed a clear discrimination between HFS groups and controls. This discrimination involved metabolites such as glucose, amino acids, pyruvate, creatine, phosphocholine/glycerophosphocholine, ketone bodies and glycoproteins as well as an increase of monounsaturated fatty acids (MUFAs) and a decrease of n-6 and n-3 polyunsaturated fatty acids (PUFAs). Although the administration of Curcuma longa did not prevent the observed increase of glucose, triglycerides, cholesterol and insulin levels, discriminating metabolites were observed between groups fed HFS alone or with addition of a Curcuma longa extract, namely some MUFA and n-3 PUFA, glycoproteins, glutamine, and methanol, suggesting that curcuminoids may act respectively on the fatty acid metabolism, the hexosamine biosynthesis pathway and alcohol oxidation. Curcuma longa extract supplementation appears to be beneficial in these metabolic pathways in rats. This metabolomic approach highlights important serum metabolites that could help in understanding further the metabolic mechanisms leading to IR. PMID:26288372

Much Ado about Nothing--Or at Best, Very Little

ERIC Educational Resources Information Center

Widaman, Keith F.

2014-01-01

Latent variable structural equation modeling has become the analytic method of choice in many domains of research in psychology and allied social sciences. One important aspect of a latent variable model concerns the relations hypothesized to hold between latent variables and their indicators. The most common specification of structural equation…

Benzodiazepine and kainate receptor binding sites in the RCS rat retina.

PubMed

Stasi, Kalliopi; Naskar, Rita; Thanos, Solon; Kouvelas, Elias D; Mitsacos, Ada

2003-02-01

The effect of age and photoreceptor degeneration on the kainate subtype of glutamate receptors and on the benzodiazepine-sensitive gamma-aminobutyric acid-A receptors (GABA(A)) in normal and RCS (Royal College of Surgeons) rats were investigated. [(3)H]Kainate and [(3)H]flunitrazepam were used as radioligands for kainate and GABA(A)/benzodiazepine()receptors, respectively, using the quantitative receptor autoradiography technique. In both normal and RCS rat retina we observed that [(3)Eta]flunitrazepam and [(3)Eta]kainate binding levels were several times higher in inner plexiform layer (IPL) than in outer plexiform layer (OPL) at all four ages studied (P17, P35, P60 and P180). Age-related changes in receptor binding were observed in normal rat retina: [(3)Eta]flunitrazepam binding showed a significant decrease of 25% between P17 and P60 in IPL,and [(3)Eta]kainate binding showed significant decreases between P17 and P35 in both synaptic layers (71% in IPL and 63% in OPL). Degeneration-related changes in benzodiazepine and kainate receptor binding were observed in RCS rat retina. In IPL, [(3)Eta]flunitrazepam and [(3)Eta]kainate binding levels were higher than in normal retina at P35 (by 24% and 86%, respectively). In OPL, [(3)Eta]flunitrazepam binding was higher in RCS than in normal retina on P35 (74%) and also on P60 (62%). The results indicate that postnatal changes occur in kainate and benzodiazepine receptor binding sites in OPL and IPL of the rat retina up to 6 months of age. The data also suggest that the receptor binding changes observed in the RCS retina could be a consequence of the primary photoreceptor degeneration.

The structure and function of the macula in patients with advanced retinitis pigmentosa.

PubMed

Vámos, Rita; Tátrai, Erika; Németh, János; Holder, Graham E; DeBuc, Delia Cabrera; Somfai, Gábor Márk

2011-10-28

To assess the structure and function of the macula in advanced retinitis pigmentosa (RP). Twenty-nine eyes of 22 patients with RP were compared against 17 control eyes. Time-domain optical coherence tomography (OCT) data were processed using OCTRIMA (optical coherence tomography retinal image analysis) as a means of quantifying commercial OCT system images. The thickness of the retinal nerve fiber layer (RNFL), ganglion cell layer and inner plexiform layer complex (GCL+IPL), inner nuclear layer and outer plexiform layer complex (INL+OPL), and the outer nuclear layer (ONL) were measured. Multifocal electroretinography (mfERG) was performed; two groups were formed based on the mfERG findings. Fourteen eyes had no detectable central retinal function (NCRF) on mfERG; detectable but abnormal retinal function (DRF) was present in the mfERG of the other 15 eyes. The thickness of the ONL in the central macular region was significantly less in the NCRF eyes compared with that in both DRF eyes and controls. The ONL was significantly thinner in the pericentral region in both patient groups compared with that in controls, whereas the thickness of the GCL+IPL and INL+OPL was significantly decreased only in the NCRF eyes. The RNFL in the peripheral region was significantly thicker, whereas the thickness of the GCL+IPL and ONL was significantly thinner in both patient groups compared with that in controls. The results are consistent with degeneration of the outer retina preceding inner retinal changes in RP. OCT image segmentation enables objective evaluation of retinal structural changes in RP, with potential use in the planning of therapeutic interventions and conceivably as an outcome measure.

The Structure and Function of the Macula in Patients with Advanced Retinitis Pigmentosa

PubMed Central

Vámos, Rita; Tátrai, Erika; Németh, János; Holder, Graham E.; DeBuc, Delia Cabrera

2011-01-01

Purpose. To assess the structure and function of the macula in advanced retinitis pigmentosa (RP). Methods. Twenty-nine eyes of 22 patients with RP were compared against 17 control eyes. Time-domain optical coherence tomography (OCT) data were processed using OCTRIMA (optical coherence tomography retinal image analysis) as a means of quantifying commercial OCT system images. The thickness of the retinal nerve fiber layer (RNFL), ganglion cell layer and inner plexiform layer complex (GCL+IPL), inner nuclear layer and outer plexiform layer complex (INL+OPL), and the outer nuclear layer (ONL) were measured. Multifocal electroretinography (mfERG) was performed; two groups were formed based on the mfERG findings. Fourteen eyes had no detectable central retinal function (NCRF) on mfERG; detectable but abnormal retinal function (DRF) was present in the mfERG of the other 15 eyes. Results. The thickness of the ONL in the central macular region was significantly less in the NCRF eyes compared with that in both DRF eyes and controls. The ONL was significantly thinner in the pericentral region in both patient groups compared with that in controls, whereas the thickness of the GCL+IPL and INL+OPL was significantly decreased only in the NCRF eyes. The RNFL in the peripheral region was significantly thicker, whereas the thickness of the GCL+IPL and ONL was significantly thinner in both patient groups compared with that in controls. Conclusions. The results are consistent with degeneration of the outer retina preceding inner retinal changes in RP. OCT image segmentation enables objective evaluation of retinal structural changes in RP, with potential use in the planning of therapeutic interventions and conceivably as an outcome measure. PMID:21948552

Iterative weighting of multiblock data in the orthogonal partial least squares framework.

PubMed

Boccard, Julien; Rutledge, Douglas N

2014-02-27

The integration of multiple data sources has emerged as a pivotal aspect to assess complex systems comprehensively. This new paradigm requires the ability to separate common and redundant from specific and complementary information during the joint analysis of several data blocks. However, inherent problems encountered when analysing single tables are amplified with the generation of multiblock datasets. Finding the relationships between data layers of increasing complexity constitutes therefore a challenging task. In the present work, an algorithm is proposed for the supervised analysis of multiblock data structures. It associates the advantages of interpretability from the orthogonal partial least squares (OPLS) framework and the ability of common component and specific weights analysis (CCSWA) to weight each data table individually in order to grasp its specificities and handle efficiently the different sources of Y-orthogonal variation. Three applications are proposed for illustration purposes. A first example refers to a quantitative structure-activity relationship study aiming to predict the binding affinity of flavonoids toward the P-glycoprotein based on physicochemical properties. A second application concerns the integration of several groups of sensory attributes for overall quality assessment of a series of red wines. A third case study highlights the ability of the method to combine very large heterogeneous data blocks from Omics experiments in systems biology. Results were compared to the reference multiblock partial least squares (MBPLS) method to assess the performance of the proposed algorithm in terms of predictive ability and model interpretability. In all cases, ComDim-OPLS was demonstrated as a relevant data mining strategy for the simultaneous analysis of multiblock structures by accounting for specific variation sources in each dataset and providing a balance between predictive and descriptive purpose. Copyright © 2014 Elsevier B.V. All rights reserved.

Modeling Nonlinear Change via Latent Change and Latent Acceleration Frameworks: Examining Velocity and Acceleration of Growth Trajectories

ERIC Educational Resources Information Center

Grimm, Kevin; Zhang, Zhiyong; Hamagami, Fumiaki; Mazzocco, Michele

2013-01-01

We propose the use of the latent change and latent acceleration frameworks for modeling nonlinear growth in structural equation models. Moving to these frameworks allows for the direct identification of "rates of change" and "acceleration" in latent growth curves--information available indirectly through traditional growth…

The Latent Structure of Attention Deficit/Hyperactivity Disorder in an Adult Sample

PubMed Central

Marcus, David K.; Norris, Alyssa L.; Coccaro, Emil F.

2012-01-01

The vast majority of studies that have examined the latent structure of attention deficit/hyperactivity disorder (ADHD) in children and adolescents have concluded that ADHD has a dimensional latent structure. In other words, ADHD symptomatology exists along a continuum and there is no natural boundary or qualitative distinction (i.e., taxon) separating youth with ADHD from those with subclinical inattention or hyperactivity/impulsivity problems. Although adult ADHD appears to be less prevalent than ADHD in youth (which could suggest a more severe adult ADHD taxon), researchers have yet to examine the latent structure of ADHD in adults. The present study used a sample (N = 600) of adults who completed a self-report measure of ADHD symptoms. The taxometric analyses revealed a dimensional latent structure for inattention, hyperactivity/impulsivity, and ADHD. These findings are consistent with previous taxometric studies that examined ADHD in children and adolescents, and with contemporary polygenic and multifactorial models of ADHD. PMID:22480749

The latent structure of attention deficit/hyperactivity disorder in an adult sample.

PubMed

Marcus, David K; Norris, Alyssa L; Coccaro, Emil F

2012-06-01

The vast majority of studies that have examined the latent structure of attention deficit/hyperactivity disorder (ADHD) in children and adolescents have concluded that ADHD has a dimensional latent structure. In other words, ADHD symptomatology exists along a continuum and there is no natural boundary or qualitative distinction (i.e., taxon) separating youth with ADHD from those with subclinical inattention or hyperactivity/impulsivity problems. Although adult ADHD appears to be less prevalent than ADHD in youth (which could suggest a more severe adult ADHD taxon), researchers have yet to examine the latent structure of ADHD in adults. The present study used a sample (N = 600) of adults who completed a self-report measure of ADHD symptoms. The taxometric analyses revealed a dimensional latent structure for inattention, hyperactivity/impulsivity, and ADHD. These findings are consistent with previous taxometric studies that examined ADHD in children and adolescents, and with contemporary polygenic and multifactorial models of ADHD. Copyright © 2012 Elsevier Ltd. All rights reserved.

Application of Local Linear Embedding to Nonlinear Exploratory Latent Structure Analysis

ERIC Educational Resources Information Center

Wang, Haonan; Iyer, Hari

2007-01-01

In this paper we discuss the use of a recent dimension reduction technique called Locally Linear Embedding, introduced by Roweis and Saul, for performing an exploratory latent structure analysis. The coordinate variables from the locally linear embedding describing the manifold on which the data reside serve as the latent variable scores. We…

Ethylene glycol revisited: Molecular dynamics simulations and visualization of the liquid and its hydrogen-bond network☆

PubMed Central

Kaiser, Alexander; Ismailova, Oksana; Koskela, Antti; Huber, Stefan E.; Ritter, Marcel; Cosenza, Biagio; Benger, Werner; Nazmutdinov, Renat; Probst, Michael

2014-01-01

Molecular dynamics simulations of liquid ethylene glycol described by the OPLS-AA force field were performed to gain insight into its hydrogen-bond structure. We use the population correlation function as a statistical measure for the hydrogen-bond lifetime. In an attempt to understand the complicated hydrogen-bonding, we developed new molecular visualization tools within the Vish Visualization shell and used it to visualize the life of each individual hydrogen-bond. With this tool hydrogen-bond formation and breaking as well as clustering and chain formation in hydrogen-bonded liquids can be observed directly. Liquid ethylene glycol at room temperature does not show significant clustering or chain building. The hydrogen-bonds break often due to the rotational and vibrational motions of the molecules leading to an H-bond half-life time of approximately 1.5 ps. However, most of the H-bonds are reformed again so that after 50 ps only 40% of these H-bonds are irreversibly broken due to diffusional motion. This hydrogen-bond half-life time due to diffusional motion is 80.3 ps. The work was preceded by a careful check of various OPLS-based force fields used in the literature. It was found that they lead to quite different angular and H-bond distributions. PMID:24748697

Reduction of parasitic interferences in digital holographic microscopy by numerically decreased coherence length

NASA Astrophysics Data System (ADS)

Kosmeier, S.; Langehanenberg, P.; von Bally, G.; Kemper, B.

2012-01-01

Due to the large coherence length of laser light, optical path length (OPL) resolution in laser based digital holographic microscopy suffers from parasitic interferences caused by multiple reflections within the experimental setup. Use of partially coherent light reduces this drawback but requires precise and stable matching of object and reference arm's OPLs and limits the spatial frequency of the interference pattern in off-axis holography. Here, we investigate if the noise properties of spectrally broadened light sources can be generated numerically. Therefore, holograms are coherently captured at different laser wavelengths and the corresponding reconstructed wave fields are numerically superimposed utilizing variable weightings. Gaussian and rectangular spectral shapes of the so synthesized field are analyzed with respect to the resulting noise level, which is quantified in OPL distributions of a reflective test target. Utilizing a Gaussian weighting, the noise level is found to be similar to the one obtained with the partially coherent light of a superluminescent diode. With a rectangular shaped synthesized spectrum, noise is reduced more efficient than with a Gaussian one. The applicability of the method in label-free cell analysis is demonstrated by quantitative phase contrast images obtained from living cancer cells.

Membrane Introduction Mass Spectrometry Combined with an Orthogonal Partial-Least Squares Calibration Model for Mixture Analysis.

PubMed

Li, Min; Zhang, Lu; Yao, Xiaolong; Jiang, Xingyu

2017-01-01

The emerging membrane introduction mass spectrometry technique has been successfully used to detect benzene, toluene, ethyl benzene and xylene (BTEX), while overlapped spectra have unfortunately hindered its further application to the analysis of mixtures. Multivariate calibration, an efficient method to analyze mixtures, has been widely applied. In this paper, we compared univariate and multivariate analyses for quantification of the individual components of mixture samples. The results showed that the univariate analysis creates poor models with regression coefficients of 0.912, 0.867, 0.440 and 0.351 for BTEX, respectively. For multivariate analysis, a comparison to the partial-least squares (PLS) model shows that the orthogonal partial-least squares (OPLS) regression exhibits an optimal performance with regression coefficients of 0.995, 0.999, 0.980 and 0.976, favorable calibration parameters (RMSEC and RMSECV) and a favorable validation parameter (RMSEP). Furthermore, the OPLS exhibits a good recovery of 73.86 - 122.20% and relative standard deviation (RSD) of the repeatability of 1.14 - 4.87%. Thus, MIMS coupled with the OPLS regression provides an optimal approach for a quantitative BTEX mixture analysis in monitoring and predicting water pollution.

A Latent Heat Retrieval and its Effects on the Intensity and Structure Change of Hurricane Guillermo (1997). Part I: The Algorithm and Observations.

NASA Technical Reports Server (NTRS)

Guimond, Stephen R.; Bourassa, mark A.; Reasor, Paul D.

2011-01-01

The release of latent heat in clouds is an essential part of the formation and I intensification ohurricanes. The community knows very little about the intensity and structure of latent heating due largely to inadequate observations. In this paper, a new method for retrieving the latent heating field in hurricanes from airborne Dopple radar is presented and fields from rapidly intensifying Hurricane Guillermo (1997) are shown.

Secondary Structure of Rat and Human Amylin across Force Fields

PubMed Central

Hoffmann, Kyle Quynn; McGovern, Michael; Chiu, Chi-cheng; de Pablo, Juan J.

2015-01-01

The aggregation of human amylin has been strongly implicated in the progression of Type II diabetes. This 37-residue peptide forms a variety of secondary structures, including random coils, α-helices, and β-hairpins. The balance between these structures depends on the chemical environment, making amylin an ideal candidate to examine inherent biases in force fields. Rat amylin differs from human amylin by only 6 residues; however, it does not form fibrils. Therefore it provides a useful complement to human amylin in studies of the key events along the aggregation pathway. In this work, the free energy of rat and human amylin was determined as a function of α-helix and β-hairpin content for the Gromos96 53a6, OPLS-AA/L, CHARMM22/CMAP, CHARMM22*, Amberff99sb*-ILDN, and Amberff03w force fields using advanced sampling techniques, specifically bias exchange metadynamics. This work represents a first systematic attempt to evaluate the conformations and the corresponding free energy of a large, clinically relevant disordered peptide in solution across force fields. The NMR chemical shifts of rIAPP were calculated for each of the force fields using their respective free energy maps, allowing us to quantitatively assess their predictions. We show that the predicted distribution of secondary structures is sensitive to the choice of force-field: Gromos53a6 is biased towards β-hairpins, while CHARMM22/CMAP predicts structures that are overly α-helical. OPLS-AA/L favors disordered structures. Amberff99sb*-ILDN, AmberFF03w and CHARMM22* provide the balance between secondary structures that is most consistent with available experimental data. In contrast to previous reports, our findings suggest that the equilibrium conformations of human and rat amylin are remarkably similar, but that subtle differences arise in transient alpha-helical and beta-strand containing structures that the human peptide can more readily adopt. We hypothesize that these transient states enable dynamic pathways that facilitate the formation of aggregates and, eventually, amyloid fibrils. PMID:26221949

Secondary structure of rat and human amylin across force fields

DOE PAGES

Hoffmann, Kyle Quynn; McGovern, Michael; Chiu, Chi -cheng; ...

2015-07-29

The aggregation of human amylin has been strongly implicated in the progression of Type II diabetes. This 37-residue peptide forms a variety of secondary structures, including random coils, α-helices, and β-hairpins. The balance between these structures depends on the chemical environment, making amylin an ideal candidate to examine inherent biases in force fields. Rat amylin differs from human amylin by only 6 residues; however, it does not form fibrils. Therefore it provides a useful complement to human amylin in studies of the key events along the aggregation pathway. In this work, the free energy of rat and human amylin wasmore » determined as a function of α-helix and β-hairpin content for the Gromos96 53a6, OPLS-AA/L, CHARMM22/CMAP, CHARMM22*, Amberff99sb*-ILDN, and Amberff03w force fields using advanced sampling techniques, specifically bias exchange metadynamics. This work represents a first systematic attempt to evaluate the conformations and the corresponding free energy of a large, clinically relevant disordered peptide in solution across force fields. The NMR chemical shifts of rIAPP were calculated for each of the force fields using their respective free energy maps, allowing us to quantitatively assess their predictions. We show that the predicted distribution of secondary structures is sensitive to the choice of force-field: Gromos53a6 is biased towards β-hairpins, while CHARMM22/CMAP predicts structures that are overly α-helical. OPLS-AA/L favors disordered structures. Amberff99sb*-ILDN, AmberFF03w and CHARMM22* provide the balance between secondary structures that is most consistent with available experimental data. In contrast to previous reports, our findings suggest that the equilibrium conformations of human and rat amylin are remarkably similar, but that subtle differences arise in transient alpha-helical and beta-strand containing structures that the human peptide can more readily adopt. We hypothesize that these transient states enable dynamic pathways that facilitate the formation of aggregates and, eventually, amyloid fibrils.« less

Three Approaches to Using Lengthy Ordinal Scales in Structural Equation Models: Parceling, Latent Scoring, and Shortening Scales

ERIC Educational Resources Information Center

Yang, Chongming; Nay, Sandra; Hoyle, Rick H.

2010-01-01

Lengthy scales or testlets pose certain challenges for structural equation modeling (SEM) if all the items are included as indicators of a latent construct. Three general approaches to modeling lengthy scales in SEM (parceling, latent scoring, and shortening) have been reviewed and evaluated. A hypothetical population model is simulated containing…

Dimensionality of the Latent Structure and Item Selection via Latent Class Multidimensional IRT Models

ERIC Educational Resources Information Center

Bartolucci, F.; Montanari, G. E.; Pandolfi, S.

2012-01-01

With reference to a questionnaire aimed at assessing the performance of Italian nursing homes on the basis of the health conditions of their patients, we investigate two relevant issues: dimensionality of the latent structure and discriminating power of the items composing the questionnaire. The approach is based on a multidimensional item…

Latent structure modeling underlying theophylline tablet formulations using a Bayesian network based on a self-organizing map clustering.

PubMed

Yasuda, Akihito; Onuki, Yoshinori; Obata, Yasuko; Takayama, Kozo

2015-01-01

The "quality by design" concept in pharmaceutical formulation development requires the establishment of a science-based rationale and design space. In this article, we integrate thin-plate spline (TPS) interpolation, Kohonen's self-organizing map (SOM) and a Bayesian network (BN) to visualize the latent structure underlying causal factors and pharmaceutical responses. As a model pharmaceutical product, theophylline tablets were prepared using a standard formulation. We measured the tensile strength and disintegration time as response variables and the compressibility, cohesion and dispersibility of the pretableting blend as latent variables. We predicted these variables quantitatively using nonlinear TPS, generated a large amount of data on pretableting blends and tablets and clustered these data into several clusters using a SOM. Our results show that we are able to predict the experimental values of the latent and response variables with a high degree of accuracy and are able to classify the tablet data into several distinct clusters. In addition, to visualize the latent structure between the causal and latent factors and the response variables, we applied a BN method to the SOM clustering results. We found that despite having inserted latent variables between the causal factors and response variables, their relation is equivalent to the results for the SOM clustering, and thus we are able to explain the underlying latent structure. Consequently, this technique provides a better understanding of the relationships between causal factors and pharmaceutical responses in theophylline tablet formulation.

Avoiding and Correcting Bias in Score-Based Latent Variable Regression with Discrete Manifest Items

ERIC Educational Resources Information Center

Lu, Irene R. R.; Thomas, D. Roland

2008-01-01

This article considers models involving a single structural equation with latent explanatory and/or latent dependent variables where discrete items are used to measure the latent variables. Our primary focus is the use of scores as proxies for the latent variables and carrying out ordinary least squares (OLS) regression on such scores to estimate…

Estimation and Model Selection for Finite Mixtures of Latent Interaction Models

ERIC Educational Resources Information Center

Hsu, Jui-Chen

2011-01-01

Latent interaction models and mixture models have received considerable attention in social science research recently, but little is known about how to handle if unobserved population heterogeneity exists in the endogenous latent variables of the nonlinear structural equation models. The current study estimates a mixture of latent interaction…

Adolescent cigarette smoking: health-related behavior or normative transgression?

PubMed

Turbin, M S; Jessor, R; Costa, F M

2000-09-01

Relations among measures of adolescent behavior were examined to determine whether cigarette smoking fits into a structure of problem behaviors-behaviors that involve normative transgression-or a structure of health-related behaviors, or both. In an ethnically and socioeconomically diverse sample of 1782 male and female high school adolescents, four first-order problem behavior latent variables-sexual intercourse experience, alcohol abuse, illicit drug use, and delinquency-were established and together were shown to reflect a second-order latent variable of problem behavior. Four first-order latent variables of health-related behaviors-unhealthy dietary habits, sedentary behavior, unsafe behavior, and poor dental hygiene-were also established and together were shown to reflect a second-order latent variable of health-compromising behavior. The structure of relations among those latent variables was modeled. Cigarette smoking had a significant and substantial loading only on the problem-behavior latent variable; its loading on the health-compromising behavior latent variable was essentially zero. Adolescent cigarette smoking relates strongly and directly to problem behaviors and only indirectly, if at all, to health-compromising behaviors. Interventions to prevent or reduce adolescent smoking should attend more to factors that influence problem behaviors.

Taxometric Analysis as a General Strategy for Distinguishing Categorical from Dimensional Latent Structure

ERIC Educational Resources Information Center

McGrath, Robert E.; Walters, Glenn D.

2012-01-01

Statistical analyses investigating latent structure can be divided into those that estimate structural model parameters and those that detect the structural model type. The most basic distinction among structure types is between categorical (discrete) and dimensional (continuous) models. It is a common, and potentially misleading, practice to…

Ionic liquid functionalized synthesis of gold nanoparticles in response to Elaise Guineensis (oil palm) leaves amount

NASA Astrophysics Data System (ADS)

Irfan, Muhammad; Ahmad, Tausif; Moniruzzaman, Muhammad; Abdullah, Bawadi

2018-05-01

A modified bio-synthesis method was developed to synthesize gold nanoparticles (AuNPs) using Elaeis Guineensis (oil palm) leaves (OPL) extract prepared in aqueous solution of IL, [EMIM][OAc]. The strong interaction and capping ability of IL at surface of AuNPs was examined through XPS analysis. The effect of OPL powder to liquid (P/L) ratio on absorbance, maximum wavelength (λmax) and size variation of AuNPs was observed through UV-vis. TEM analysis indicated predominantly spherical shape AuNPs with mean diameter of 15.76 nm. This study exhibits a rapid, cheap and efficient method to achieve stable AuNPs using bio-waste material.

ATS-1/ATS-3 dual satellite navigation study

NASA Technical Reports Server (NTRS)

Hoover, W. M.

1971-01-01

A study which illustrated the feasibility of implementing an on-board aircraft navigation system based on using the ATS-1 and ATS-3 satellites, the modified Omega Position Location Equipment (OPLE) Control Center, and a suitable aircraft terminal was conducted. The report provides: (1) a consideration of the problems of satellite navigation and an objective definition of the optimum system under the constraints of its specified components, (2) a description of the necessary modifications to the OPLE Control Center, the design of an aircraft terminal, and the design of ground reference terminals, and (3) an outline of an experiment plan and an estimate of the cost to be expected in conducting the program.

Do gender and directness of trauma exposure moderate PTSD's latent structure?

PubMed

Frankfurt, Sheila B; Armour, Cherie; Contractor, Ateka A; Elhai, Jon D

2016-11-30

The PTSD diagnosis and latent structure were substantially revised in the transition from DSM-IV to DSM-5. However, three alternative models (i.e., anhedonia model, externalizing behavior model, and hybrid model) of PTSD fit the DSM-5 symptom criteria better than the DSM-5 factor model. Thus, the psychometric performance of the DSM-5 and alternative models' PTSD factor structure needs to be critically evaluated. The current study examined whether gender or trauma directness (i.e., direct or indirect trauma exposure) moderates the PTSD latent structure when using the DSM-5 or alternative models. Model performance was evaluated with measurement invariance testing procedures on a large undergraduate sample (n=455). Gender and trauma directness moderated the DSM-5 PTSD and externalizing behavior model and did not moderate the anhedonia and hybrid models' latent structure. Clinical implications and directions for future research are discussed. Published by Elsevier Ireland Ltd.

Mokken scaling analysis of the Hospital Anxiety and Depression Scale in individuals with cardiovascular disease.

PubMed

Cosco, Theodore D; Doyle, Frank; Watson, Roger; Ward, Mark; McGee, Hannah

2012-01-01

The Hospital Anxiety and Depression Scale (HADS) is a prolifically used scale of anxiety and depression. The original bidimensional anxiety-depression latent structure of the HADS has come under significant scrutiny, with previous studies revealing one-, two-, three- and four-dimensional structures. The current study examines the latent structure of the HADS using a non-parametric item response theory method. Using data conglomerated from four independent studies of cardiovascular disease employing the HADS (n=893), Mokken scaling procedure was conducted to assess the latent structure of the HADS. A single scale consisting of 12 of 14 HADS items was revealed, indicating a unidimensional latent HADS structure. The HADS was initially intended to measure mutually exclusive levels of anxiety and depression; however, the current study indicates that a single dimension of general psychological distress is captured. Copyright © 2012 Elsevier Inc. All rights reserved.

The algebraic theory of latent projectors in lambda matrices

NASA Technical Reports Server (NTRS)

Denman, E. D.; Leyva-Ramos, J.; Jeon, G. J.

1981-01-01

Multivariable systems such as a finite-element model of vibrating structures, control systems, and large-scale systems are often formulated in terms of differential equations which give rise to lambda matrices. The present investigation is concerned with the formulation of the algebraic theory of lambda matrices and the relationship of latent roots, latent vectors, and latent projectors to the eigenvalues, eigenvectors, and eigenprojectors of the companion form. The chain rule for latent projectors and eigenprojectors for the repeated latent root or eigenvalues is given.

Characterising the latent structure and organisation of self-reported thoughts, feelings and behaviours in adolescents and young adults

PubMed Central

Neufeld, Sharon; Jones, Peter B.; Fonagy, Peter; Bullmore, Edward T.; Dolan, Raymond J.; Moutoussis, Michael; Toseeb, Umar; Goodyer, Ian M.

2017-01-01

Little is known about the underlying relationships between self-reported mental health items measuring both positive and negative emotional and behavioural symptoms at the population level in young people. Improved measurement of the full range of mental well-being and mental illness may aid in understanding the aetiological substrates underlying the development of both mental wellness as well as specific psychiatric diagnoses. A general population sample aged 14 to 24 years completed self-report questionnaires on anxiety, depression, psychotic-like symptoms, obsessionality and well-being. Exploratory and confirmatory factor models for categorical data and latent profile analyses were used to evaluate the structure of both mental wellness and illness items. First order, second order and bifactor structures were evaluated on 118 self-reported items obtained from 2228 participants. A bifactor solution was the best fitting latent variable model with one general latent factor termed ‘distress’ and five ‘distress independent’ specific factors defined as self-confidence, antisocial behaviour, worry, aberrant thinking, and mood. Next, six distinct subgroups were derived from a person-centred latent profile analysis of the factor scores. Finally, concurrent validity was assessed using information on hazardous behaviours (alcohol use, substance misuse, self-harm) and treatment for mental ill health: both discriminated between the latent traits and latent profile subgroups. The findings suggest a complex, multidimensional mental health structure in the youth population rather than the previously assumed first or second order factor structure. Additionally, the analysis revealed a low hazardous behaviour/low mental illness risk subgroup not previously described. Population sub-groups show greater validity over single variable factors in revealing mental illness risks. In conclusion, our findings indicate that the structure of self reported mental health is multidimensional in nature and uniquely finds improved prediction to mental illness risk within person-centred subgroups derived from the multidimensional latent traits. PMID:28403164

Characterising the latent structure and organisation of self-reported thoughts, feelings and behaviours in adolescents and young adults.

PubMed

St Clair, Michelle C; Neufeld, Sharon; Jones, Peter B; Fonagy, Peter; Bullmore, Edward T; Dolan, Raymond J; Moutoussis, Michael; Toseeb, Umar; Goodyer, Ian M

2017-01-01

Little is known about the underlying relationships between self-reported mental health items measuring both positive and negative emotional and behavioural symptoms at the population level in young people. Improved measurement of the full range of mental well-being and mental illness may aid in understanding the aetiological substrates underlying the development of both mental wellness as well as specific psychiatric diagnoses. A general population sample aged 14 to 24 years completed self-report questionnaires on anxiety, depression, psychotic-like symptoms, obsessionality and well-being. Exploratory and confirmatory factor models for categorical data and latent profile analyses were used to evaluate the structure of both mental wellness and illness items. First order, second order and bifactor structures were evaluated on 118 self-reported items obtained from 2228 participants. A bifactor solution was the best fitting latent variable model with one general latent factor termed 'distress' and five 'distress independent' specific factors defined as self-confidence, antisocial behaviour, worry, aberrant thinking, and mood. Next, six distinct subgroups were derived from a person-centred latent profile analysis of the factor scores. Finally, concurrent validity was assessed using information on hazardous behaviours (alcohol use, substance misuse, self-harm) and treatment for mental ill health: both discriminated between the latent traits and latent profile subgroups. The findings suggest a complex, multidimensional mental health structure in the youth population rather than the previously assumed first or second order factor structure. Additionally, the analysis revealed a low hazardous behaviour/low mental illness risk subgroup not previously described. Population sub-groups show greater validity over single variable factors in revealing mental illness risks. In conclusion, our findings indicate that the structure of self reported mental health is multidimensional in nature and uniquely finds improved prediction to mental illness risk within person-centred subgroups derived from the multidimensional latent traits.

The Theory of Planned Behavior within the Stages of the Transtheoretical Model: Latent Structural Modeling of Stage-Specific Prediction Patterns in Physical Activity

ERIC Educational Resources Information Center

Lippke, Sonia; Nigg, Claudio R.; Maddock, Jay E.

2007-01-01

This is the first study to test whether the stages of change of the transtheoretical model are qualitatively different through exploring discontinuity patterns in theory of planned behavior (TPB) variables using latent multigroup structural equation modeling (MSEM) with AMOS. Discontinuity patterns in terms of latent means and prediction patterns…

Examining Factor Score Distributions to Determine the Nature of Latent Spaces

ERIC Educational Resources Information Center

Steinley, Douglas; McDonald, Roderick P.

2007-01-01

Similarities between latent class models with K classes and linear factor models with K-1 factors are investigated. Specifically, the mathematical equivalence between the covariance structure of the two models is discussed, and a Monte Carlo simulation is performed using generated data that represents both latent factors and latent classes with…

Sensitivity of Latent Heating Profiles to Environmental Conditions: Implications for TRMM and Climate Research

NASA Technical Reports Server (NTRS)

Shepherd, J. Marshall; Einaudi, Franco (Technical Monitor)

2000-01-01

The Tropical Rainfall Measuring Mission (TRMM) as a part of NASA's Earth System Enterprise is the first mission dedicated to measuring tropical rainfall through microwave and visible sensors, and includes the first spaceborne rain radar. Tropical rainfall comprises two-thirds of global rainfall. It is also the primary distributor of heat through the atmosphere's circulation. It is this circulation that defines Earth's weather and climate. Understanding rainfall and its variability is crucial to understanding and predicting global climate change. Weather and climate models need an accurate assessment of the latent heating released as tropical rainfall occurs. Currently, cloud model-based algorithms are used to derive latent heating based on rainfall structure. Ultimately, these algorithms can be applied to actual data from TRMM. This study investigates key underlying assumptions used in developing the latent heating algorithms. For example, the standard algorithm is highly dependent on a system's rainfall amount and structure. It also depends on an a priori database of model-derived latent heating profiles based on the aforementioned rainfall characteristics. Unanswered questions remain concerning the sensitivity of latent heating profiles to environmental conditions (both thermodynamic and kinematic), regionality, and seasonality. This study investigates and quantifies such sensitivities and seeks to determine the optimal latent heating profile database based on the results. Ultimately, the study seeks to produce an optimized latent heating algorithm based not only on rainfall structure but also hydrometeor profiles.

Retina-Inspired Filter.

PubMed

Doutsi, Effrosyni; Fillatre, Lionel; Antonini, Marc; Gaulmin, Julien

2018-07-01

This paper introduces a novel filter, which is inspired by the human retina. The human retina consists of three different layers: the Outer Plexiform Layer (OPL), the inner plexiform layer, and the ganglionic layer. Our inspiration is the linear transform which takes place in the OPL and has been mathematically described by the neuroscientific model "virtual retina." This model is the cornerstone to derive the non-separable spatio-temporal OPL retina-inspired filter, briefly renamed retina-inspired filter, studied in this paper. This filter is connected to the dynamic behavior of the retina, which enables the retina to increase the sharpness of the visual stimulus during filtering before its transmission to the brain. We establish that this retina-inspired transform forms a group of spatio-temporal Weighted Difference of Gaussian (WDoG) filters when it is applied to a still image visible for a given time. We analyze the spatial frequency bandwidth of the retina-inspired filter with respect to time. It is shown that the WDoG spectrum varies from a lowpass filter to a bandpass filter. Therefore, while time increases, the retina-inspired filter enables to extract different kinds of information from the input image. Finally, we discuss the benefits of using the retina-inspired filter in image processing applications such as edge detection and compression.

Molecular dynamics simulation for the test of calibrated OPLS-AA force field for binary liquid mixture of tri-iso-amyl phosphate and n-dodecane.

PubMed

Das, Arya; Ali, Sk Musharaf

2018-02-21

Tri-isoamyl phosphate (TiAP) has been proposed to be an alternative for tri-butyl phosphate (TBP) in the Plutonium Uranium Extraction (PUREX) process. Recently, we have successfully calibrated and tested all-atom optimized potentials for liquid simulations using Mulliken partial charges for pure TiAP, TBP, and dodecane by performing molecular dynamics (MD) simulation. It is of immense importance to extend this potential for the various molecular properties of TiAP and TiAP/n-dodecane binary mixtures using MD simulation. Earlier, efforts were devoted to find out a suitable force field which can explain both structural and dynamical properties by empirical parameterization. Therefore, the present MD study reports the structural, dynamical, and thermodynamical properties with different mole fractions of TiAP-dodecane mixtures at the entire range of mole fraction of 0-1 employing our calibrated Mulliken embedded optimized potentials for liquid simulation (OPLS) force field. The calculated electric dipole moment of TiAP was seen to be almost unaffected by the TiAP concentration in the dodecane diluent. The calculated liquid densities of the TiAP-dodecane mixture are in good agreement with the experimental data. The mixture densities at different temperatures are also studied which was found to be reduced with temperature as expected. The plot of diffusivities for TiAP and dodecane against mole fraction in the binary mixture intersects at a composition in the range of 25%-30% of TiAP in dodecane, which is very much closer to the TBP/n-dodecane composition used in the PUREX process. The excess volume of mixing was found to be positive for the entire range of mole fraction and the excess enthalpy of mixing was shown to be endothermic for the TBP/n-dodecane mixture as well as TiAP/n-dodecane mixture as reported experimentally. The spatial pair correlation functions are evaluated between TiAP-TiAP and TiAP-dodecane molecules. Further, shear viscosity has been computed by performing the non-equilibrium molecular dynamics employing the periodic perturbation method. The calculated shear viscosity of the binary mixture is found to be in excellent agreement with the experimental values. The use of the newly calibrated OPLS force field embedding Mulliken charges is shown to be equally reliable in predicting the structural and dynamical properties for the mixture without incorporating any arbitrary scaling in the force field or Lennard-Jones parameters. Further, the present MD simulation results demonstrate that the Stokes-Einstein relation breaks down at the molecular level. The present methodology might be adopted to evaluate the liquid state properties of an aqueous-organic biphasic system, which is of great significance in the interfacial science and technology.

Molecular dynamics simulation for the test of calibrated OPLS-AA force field for binary liquid mixture of tri-iso-amyl phosphate and n-dodecane

NASA Astrophysics Data System (ADS)

Das, Arya; Ali, Sk. Musharaf

2018-02-01

Tri-isoamyl phosphate (TiAP) has been proposed to be an alternative for tri-butyl phosphate (TBP) in the Plutonium Uranium Extraction (PUREX) process. Recently, we have successfully calibrated and tested all-atom optimized potentials for liquid simulations using Mulliken partial charges for pure TiAP, TBP, and dodecane by performing molecular dynamics (MD) simulation. It is of immense importance to extend this potential for the various molecular properties of TiAP and TiAP/n-dodecane binary mixtures using MD simulation. Earlier, efforts were devoted to find out a suitable force field which can explain both structural and dynamical properties by empirical parameterization. Therefore, the present MD study reports the structural, dynamical, and thermodynamical properties with different mole fractions of TiAP-dodecane mixtures at the entire range of mole fraction of 0-1 employing our calibrated Mulliken embedded optimized potentials for liquid simulation (OPLS) force field. The calculated electric dipole moment of TiAP was seen to be almost unaffected by the TiAP concentration in the dodecane diluent. The calculated liquid densities of the TiAP-dodecane mixture are in good agreement with the experimental data. The mixture densities at different temperatures are also studied which was found to be reduced with temperature as expected. The plot of diffusivities for TiAP and dodecane against mole fraction in the binary mixture intersects at a composition in the range of 25%-30% of TiAP in dodecane, which is very much closer to the TBP/n-dodecane composition used in the PUREX process. The excess volume of mixing was found to be positive for the entire range of mole fraction and the excess enthalpy of mixing was shown to be endothermic for the TBP/n-dodecane mixture as well as TiAP/n-dodecane mixture as reported experimentally. The spatial pair correlation functions are evaluated between TiAP-TiAP and TiAP-dodecane molecules. Further, shear viscosity has been computed by performing the non-equilibrium molecular dynamics employing the periodic perturbation method. The calculated shear viscosity of the binary mixture is found to be in excellent agreement with the experimental values. The use of the newly calibrated OPLS force field embedding Mulliken charges is shown to be equally reliable in predicting the structural and dynamical properties for the mixture without incorporating any arbitrary scaling in the force field or Lennard-Jones parameters. Further, the present MD simulation results demonstrate that the Stokes-Einstein relation breaks down at the molecular level. The present methodology might be adopted to evaluate the liquid state properties of an aqueous-organic biphasic system, which is of great significance in the interfacial science and technology.

Residual Structures in Latent Growth Curve Modeling

ERIC Educational Resources Information Center

Grimm, Kevin J.; Widaman, Keith F.

2010-01-01

Several alternatives are available for specifying the residual structure in latent growth curve modeling. Two specifications involve uncorrelated residuals and represent the most commonly used residual structures. The first, building on repeated measures analysis of variance and common specifications in multilevel models, forces residual variances…

Non-image Forming Light Detection by Melanopsin, Rhodopsin, and Long-Middlewave (L/W) Cone Opsin in the Subterranean Blind Mole Rat, Spalax Ehrenbergi: Immunohistochemical Characterization, Distribution, and Connectivity

PubMed Central

Esquiva, Gema; Avivi, Aaron; Hannibal, Jens

2016-01-01

The blind mole rat, Spalax ehrenbergi, can, despite severely degenerated eyes covered by fur, entrain to the daily light/dark cycle and adapt to seasonal changes due to an intact circadian timing system. The present study demonstrates that the Spalax retina contains a photoreceptor layer, an outer nuclear layer (ONL), an outer plexiform layer (OPL), an inner nuclear layer (INL), an inner plexiform layer (IPL), and a ganglion cell layer (GCL). By immunohistochemistry, the number of melanopsin (mRGCs) and non-melanopsin bearing retinal ganglion cells was analyzed in detail. Using the ganglion cell marker RNA-binding protein with multiple splicing (RBPMS) it was shown that the Spalax eye contains 890 ± 62 RGCs. Of these, 87% (752 ± 40) contain melanopsin (cell density 788 melanopsin RGCs/mm2). The remaining RGCs were shown to co-store Brn3a and calretinin. The melanopsin cells were located mainly in the GCL with projections forming two dendritic plexuses located in the inner part of the IPL and in the OPL. Few melanopsin dendrites were also found in the ONL. The Spalax retina is rich in rhodopsin and long/middle wave (L/M) cone opsin bearing photoreceptor cells. By using Ctbp2 as a marker for ribbon synapses, both rods and L/M cone ribbons containing pedicles in the OPL were found in close apposition with melanopsin dendrites in the outer plexus suggesting direct synaptic contact. A subset of cone bipolar cells and all photoreceptor cells contain recoverin while a subset of bipolar and amacrine cells contain calretinin. The calretinin expressing amacrine cells seemed to form synaptic contacts with rhodopsin containing photoreceptor cells in the OPL and contacts with melanopsin cell bodies and dendrites in the IPL. The study demonstrates the complex retinal circuitry used by the Spalax to detect light, and provides evidence for both melanopsin and non-melanopsin projecting pathways to the brain. PMID:27375437

Non-image Forming Light Detection by Melanopsin, Rhodopsin, and Long-Middlewave (L/W) Cone Opsin in the Subterranean Blind Mole Rat, Spalax Ehrenbergi: Immunohistochemical Characterization, Distribution, and Connectivity.

PubMed

Esquiva, Gema; Avivi, Aaron; Hannibal, Jens

2016-01-01

The blind mole rat, Spalax ehrenbergi, can, despite severely degenerated eyes covered by fur, entrain to the daily light/dark cycle and adapt to seasonal changes due to an intact circadian timing system. The present study demonstrates that the Spalax retina contains a photoreceptor layer, an outer nuclear layer (ONL), an outer plexiform layer (OPL), an inner nuclear layer (INL), an inner plexiform layer (IPL), and a ganglion cell layer (GCL). By immunohistochemistry, the number of melanopsin (mRGCs) and non-melanopsin bearing retinal ganglion cells was analyzed in detail. Using the ganglion cell marker RNA-binding protein with multiple splicing (RBPMS) it was shown that the Spalax eye contains 890 ± 62 RGCs. Of these, 87% (752 ± 40) contain melanopsin (cell density 788 melanopsin RGCs/mm(2)). The remaining RGCs were shown to co-store Brn3a and calretinin. The melanopsin cells were located mainly in the GCL with projections forming two dendritic plexuses located in the inner part of the IPL and in the OPL. Few melanopsin dendrites were also found in the ONL. The Spalax retina is rich in rhodopsin and long/middle wave (L/M) cone opsin bearing photoreceptor cells. By using Ctbp2 as a marker for ribbon synapses, both rods and L/M cone ribbons containing pedicles in the OPL were found in close apposition with melanopsin dendrites in the outer plexus suggesting direct synaptic contact. A subset of cone bipolar cells and all photoreceptor cells contain recoverin while a subset of bipolar and amacrine cells contain calretinin. The calretinin expressing amacrine cells seemed to form synaptic contacts with rhodopsin containing photoreceptor cells in the OPL and contacts with melanopsin cell bodies and dendrites in the IPL. The study demonstrates the complex retinal circuitry used by the Spalax to detect light, and provides evidence for both melanopsin and non-melanopsin projecting pathways to the brain.

Estimates of free-tropospheric NO2 and HCHO mixing ratios derived from high-altitude mountain MAX-DOAS observations at midlatitudes and in the tropics

NASA Astrophysics Data System (ADS)

Schreier, Stefan F.; Richter, Andreas; Wittrock, Folkard; Burrows, John P.

2016-03-01

In this study, mixing ratios of NO2 (XNO2) and HCHO (XHCHO) in the free troposphere are derived from two multi-axis differential optical absorption spectroscopy (MAX-DOAS) data sets collected at Zugspitze (2650 m a.s.l., Germany) and Pico Espejo (4765 m a.s.l., Venezuela). The estimation of NO2 and HCHO mixing ratios is based on the modified geometrical approach, which assumes a single-scattering geometry and a scattering point altitude close to the instrument altitude. Firstly, the horizontal optical path length (hOPL) is obtained from O4 differential slant column densities (DSCDs) in the horizontal (0°) and vertical (90°) viewing directions. Secondly, XNO2 and XHCHO are estimated from the NO2 and HCHO DSCDs at the 0° and 90° viewing directions and averaged along the obtained hOPLs. As the MAX-DOAS instrument was performing measurements in the ultraviolet region, wavelength ranges of 346-372 and 338-357 nm are selected for the DOAS analysis to retrieve NO2 and HCHO DSCDs, respectively. In order to compare the measured O4 DSCDs and moreover to perform some sensitivity tests, the radiative transfer model SCIATRAN with adapted altitude settings for mountainous terrain is operated to simulate synthetic spectra, on which the DOAS analysis is also applied. The overall agreement between measured and synthetic O4 DSCDs is better for the higher Pico Espejo station than for Zugspitze. Further sensitivity analysis shows that a change in surface albedo (from 0.05 to 0.7) can influence the O4 DSCDs, with a larger absolute difference observed for the horizontal viewing direction. Consequently, the hOPL can vary by about 5 % throughout the season, for example when winter snow cover fully disappears in summer. Typical values of hOPLs during clear-sky conditions are 19 km (14 km) at Zugspitze and 34 km (26.5 km) at Pico Espejo when using the 346-372 (338-357 nm) fitting window. The estimated monthly values of XNO2 (XHCHO), averaged over these hOPLs during clear-sky conditions, are in the range of 60-100 ppt (500-950 ppt) at Zugspitze and 8.5-15.5 ppt (255-385 ppt) at Pico Espejo. Interestingly, multi-year-averaged monthly means of XNO2 and XHCHO increase towards the end of the dry season at the Pico Espejo site, suggesting that both trace gases are frequently lifted above the boundary layer as a result of South American biomass burning.

Estimates of free-tropospheric NO2 and HCHO mixing ratios derived from high-altitude mountain MAX-DOAS observations in the mid-latitudes and tropics

NASA Astrophysics Data System (ADS)

Schreier, S. F.; Richter, A.; Wittrock, F.; Burrows, J. P.

2015-11-01

In this study, mixing ratios of NO2 (XNO2) and HCHO (XHCHO) in the free troposphere are derived from two Multi-AXis Differential Optical Absorption Spectroscopy (MAX-DOAS) data sets collected at Zugspitze (2650 m a.s.l., Germany) and Pico Espejo (4765 m a.s.l., Venezuela). The estimation of NO2 and HCHO mixing ratios is based on the modified geometrical approach, which assumes a single-scattering geometry and a scattering point altitude close to the instrument. Firstly, the horizontal optical path length (hOPL) is obtained from O4 differential slant column densities (DSCDs) in the horizontal (0°) and vertical (90°) viewing directions. Secondly, XNO2 and XHCHO are estimated from the NO2 and HCHO DSCDs at the 0 and 90° viewing directions and averaged along the obtained hOPLs. As the MAX-DOAS instrument was performing measurements in the ultraviolet region, wavelength ranges of 346-372 and 338-357 nm are selected for the DOAS analysis to retrieve NO2 and HCHO DSCDs, respectively. In order to compare the measured O4 DSCDs and moreover to perform some sensitivity tests, the radiative transfer model SCIATRAN with adapted altitude settings for mountainous terrain is operated to simulate synthetic spectra, on which the DOAS analysis is also applied. The overall agreement between measured and synthetic O4 DSCDs is better for the higher Pico Espejo station than for Zugspitze. Further sensitivity analysis shows that a change in surface albedo (from 0.05 to 0.7) can influence the O4 DSCDs, with a larger absolute difference observed for the horizontal viewing direction. Consequently, the hOPL can vary by about 5 % throughout the season, for example when winter snow cover fully disappears in summer. Typical values of hOPLs during clear sky conditions are 19 km (14 km) at Zugspitze and 34 km (26.5 km) at Pico Espejo when using the 346-372 nm (338-357 nm) fitting window. The estimated monthly values of XNO2 (XHCHO), averaged over these hOPLs during clear sky conditions, are in the range of 60-100 ppt (500-950 ppt) at Zugspitze and 8.5-15.5 ppt (255-385 ppt) at Pico Espejo. Interestingly, multi-year averaged monthly means of XNO2 and XHCHO increase towards the end of the dry season at the Pico Espejo site, suggesting that both trace gases are frequently lifted above the boundary layer as a result of South American biomass burning.

How accurately do force fields represent protein side chain ensembles?

PubMed

Petrović, Dušan; Wang, Xue; Strodel, Birgit

2018-05-23

Although the protein backbone is the most fundamental part of the structure, the fine-tuning of side-chain conformations is important for protein function, for example, in protein-protein and protein-ligand interactions, and also in enzyme catalysis. While several benchmarks testing the performance of protein force fields for side chain properties have already been published, they often considered only a few force fields and were not tested against the same experimental observables; hence, they are not directly comparable. In this work, we explore the ability of twelve force fields, which are different flavors of AMBER, CHARMM, OPLS, or GROMOS, to reproduce average rotamer angles and rotamer populations obtained from extensive NMR studies of the 3 J and residual dipolar coupling constants for two small proteins: ubiquitin and GB3. Based on a total of 196 μs sampling time, our results reveal that all force fields identify the correct side chain angles, while the AMBER and CHARMM force fields clearly outperform the OPLS and GROMOS force fields in estimating rotamer populations. The three best force fields for representing the protein side chain dynamics are AMBER 14SB, AMBER 99SB*-ILDN, and CHARMM36. Furthermore, we observe that the side chain ensembles of buried amino acid residues are generally more accurately represented than those of the surface exposed residues. This article is protected by copyright. All rights reserved. © 2018 Wiley Periodicals, Inc.

Does Attention-Deficit/Hyperactivity Disorder Have a Dimensional Latent Structure? A Taxometric Analysis

PubMed Central

Marcus, David K.; Barry, Tammy D.

2010-01-01

An understanding of the latent structure of attention-deficit/hyperactivity disorder (ADHD) is essential for developing causal models of this disorder. Although some researchers have presumed that ADHD is dimensional and others have assumed that it is taxonic, there has been relatively little research directly examining the latent structure of ADHD. The authors conducted a set of taxometric analyses using data from the NICHD Study of Early Child Care and Youth Development (ns between 667–1078). The results revealed a dimensional latent structure across a variety of different analyses and sets of indicators, for inattention, hyperactivity/impulsivity, and ADHD. Furthermore, analyses of correlations with associated features indicated that dimensional models demonstrated stronger validity coefficients with these criterion measures than dichotomous models. These findings jibe with recent research on the genetic basis of ADHD and with contemporary models of ADHD. PMID:20973595

Does attention-deficit/hyperactivity disorder have a dimensional latent structure? A taxometric analysis.

PubMed

Marcus, David K; Barry, Tammy D

2011-05-01

An understanding of the latent structure of attention-deficit/hyperactivity disorder (ADHD) is essential for developing causal models of this disorder. Although some researchers have presumed that ADHD is dimensional and others have assumed that it is taxonic, there has been relatively little research directly examining the latent structure of ADHD. The authors conducted a set of taxometric analyses using data from the NICHD Study of Early Child Care and Youth Development (ns between 667 and 1,078). The results revealed a dimensional latent structure across a variety of different analyses and sets of indicators for inattention, hyperactivity/impulsivity, and ADHD. Furthermore, analyses of correlations with associated features indicated that dimensional models demonstrated stronger validity coefficients with these criterion measures than dichotomous models. These findings jibe with recent research on the genetic basis of ADHD and with contemporary models of ADHD.

Generalized Structured Component Analysis with Latent Interactions

ERIC Educational Resources Information Center

Hwang, Heungsun; Ho, Moon-Ho Ringo; Lee, Jonathan

2010-01-01

Generalized structured component analysis (GSCA) is a component-based approach to structural equation modeling. In practice, researchers may often be interested in examining the interaction effects of latent variables. However, GSCA has been geared only for the specification and testing of the main effects of variables. Thus, an extension of GSCA…

A Bayesian Model for the Estimation of Latent Interaction and Quadratic Effects When Latent Variables Are Non-Normally Distributed

ERIC Educational Resources Information Center

Kelava, Augustin; Nagengast, Benjamin

2012-01-01

Structural equation models with interaction and quadratic effects have become a standard tool for testing nonlinear hypotheses in the social sciences. Most of the current approaches assume normally distributed latent predictor variables. In this article, we present a Bayesian model for the estimation of latent nonlinear effects when the latent…

NANOGOLD decorated by pHLIP peptide: comparative force field study.

PubMed

Kyrychenko, A

2015-05-21

The potential of gold nanoparticles (AuNPs) in therapeutic and diagnostic cancer applications is becoming increasingly recognized, which focuses on their efficient and specific delivery from passive accumulation in tumour tissue to directly targeting tumor-specific biomarkers. AuNPs functionalized by pH low insertion peptide (pHLIP) have recently revealed the capability of targeting acidic tissues and inserting into cell membranes. However, the structure of AuNP-pHLIP conjugates and fundamental gold-peptide interactions still remain unknown. In this study, we have developed a series of molecular dynamics (MD) models reproducing a small gold nanoparticle coupled to pHLIP. We focus on Au135 nanoparticles that comprise a nearly spherical Au core (diameter ∼ 1.4 nm) functionalized with a monomaleimide moiety, mimicking a commercially available monomaleimido NANOGOLD® labelling agent. To probe the structure and folding of pHLIP, which is attached covalently to the maleimide NANOGOLD particle, we have benchmarked the performances of a series of popular, all-atom force fields (FF), including those of OPLS-AA, AMBER03, three variations of CHARMM FFs, as well as united-atom GROMOS G53A6 FF. We found that CHARMMs and OPLSAA FFs predict that in an aqueous salt solution at a neutral pH, pHLIP is partially bound onto the gold surface through some short hydrophobic peptide stretches, while at the same time, a large portion of peptide remains in solution. In contrast, AMBER03 and G53A6 FFs revealed the formation of compact, tightly bound peptide configurations adsorbed onto the nanoparticle core. To reproduce the experimental physical picture of the peptide adsorption onto gold in unfolded and unstructured conformations, our study suggests CHARMM36 and OPLS-AA FFs as a tool of choice for the computational studies of NANOGOLD decorated by pHLIP.

Electronic effects on melting: Comparison of aluminum cluster anions and cations

NASA Astrophysics Data System (ADS)

Starace, Anne K.; Neal, Colleen M.; Cao, Baopeng; Jarrold, Martin F.; Aguado, Andrés; López, José M.

2009-07-01

Heat capacities have been measured as a function of temperature for aluminum cluster anions with 35-70 atoms. Melting temperatures and latent heats are determined from peaks in the heat capacities; cohesive energies are obtained for solid clusters from the latent heats and dissociation energies determined for liquid clusters. The melting temperatures, latent heats, and cohesive energies for the aluminum cluster anions are compared to previous measurements for the corresponding cations. Density functional theory calculations have been performed to identify the global minimum energy geometries for the cluster anions. The lowest energy geometries fall into four main families: distorted decahedral fragments, fcc fragments, fcc fragments with stacking faults, and "disordered" roughly spherical structures. The comparison of the cohesive energies for the lowest energy geometries with the measured values allows us to interpret the size variation in the latent heats. Both geometric and electronic shell closings contribute to the variations in the cohesive energies (and latent heats), but structural changes appear to be mainly responsible for the large variations in the melting temperatures with cluster size. The significant charge dependence of the latent heats found for some cluster sizes indicates that the electronic structure can change substantially when the cluster melts.

Automated classifiers for early detection and diagnosis of retinopathy in diabetic eyes.

PubMed

Somfai, Gábor Márk; Tátrai, Erika; Laurik, Lenke; Varga, Boglárka; Ölvedy, Veronika; Jiang, Hong; Wang, Jianhua; Smiddy, William E; Somogyi, Anikó; DeBuc, Delia Cabrera

2014-04-12

Artificial neural networks (ANNs) have been used to classify eye diseases, such as diabetic retinopathy (DR) and glaucoma. DR is the leading cause of blindness in working-age adults in the developed world. The implementation of DR diagnostic routines could be feasibly improved by the integration of structural and optical property test measurements of the retinal structure that provide important and complementary information for reaching a diagnosis. In this study, we evaluate the capability of several structural and optical features (thickness, total reflectance and fractal dimension) of various intraretinal layers extracted from optical coherence tomography images to train a Bayesian ANN to discriminate between healthy and diabetic eyes with and with no mild retinopathy. When exploring the probability as to whether the subject's eye was healthy (diagnostic condition, Test 1), we found that the structural and optical property features of the outer plexiform layer (OPL) and the complex formed by the ganglion cell and inner plexiform layers (GCL + IPL) provided the highest probability (positive predictive value (PPV) of 91% and 89%, respectively) for the proportion of patients with positive test results (healthy condition) who were correctly diagnosed (Test 1). The true negative, TP and PPV values remained stable despite the different sizes of training data sets (Test 2). The sensitivity, specificity and PPV were greater or close to 0.70 for the retinal nerve fiber layer's features, photoreceptor outer segments and retinal pigment epithelium when 23 diabetic eyes with mild retinopathy were mixed with 38 diabetic eyes with no retinopathy (Test 3). A Bayesian ANN trained on structural and optical features from optical coherence tomography data can successfully discriminate between healthy and diabetic eyes with and with no retinopathy. The fractal dimension of the OPL and the GCL + IPL complex predicted by the Bayesian radial basis function network provides better diagnostic utility to classify diabetic eyes with mild retinopathy. Moreover, the thickness and fractal dimension parameters of the retinal nerve fiber layer, photoreceptor outer segments and retinal pigment epithelium show promise for the diagnostic classification between diabetic eyes with and with no mild retinopathy.

Bayesian Analysis of Structural Equation Models with Nonlinear Covariates and Latent Variables

ERIC Educational Resources Information Center

Song, Xin-Yuan; Lee, Sik-Yum

2006-01-01

In this article, we formulate a nonlinear structural equation model (SEM) that can accommodate covariates in the measurement equation and nonlinear terms of covariates and exogenous latent variables in the structural equation. The covariates can come from continuous or discrete distributions. A Bayesian approach is developed to analyze the…

Infrared-metabolomics approach in detecting changes in Andrographis paniculata metabolites due to different harvesting ages and times.

PubMed

Yusof, Nur A'thifah; Isha, Azizul; Ismail, Intan Safinar; Khatib, Alfi; Shaari, Khozirah; Abas, Faridah; Rukayadi, Yaya

2015-09-01

The metabolite changes in three germplasm accessions of Malaysia Andrographis paniculata (Burm. F.) Nees, viz. 11265 (H), 11341 (P) and 11248 (T), due to their different harvesting ages and times were successfully evaluated by attenuated total reflectance (ATR)-Fourier transform infrared (FTIR) spectroscopy and translated through multivariate data analysis of principal component analysis (PCA) and orthogonal partial least square-discriminant analysis (OPLS-DA). This present study revealed the feasibility of ATR-FTIR in detecting the trend changes of the major metabolites - andrographolide and neoandrographolide - functional groups in A. paniculata leaves of different accessions. The harvesting parameter was set at three different ages of 120, 150 and 180 days after transplanting (DAT) and at two different time sessions of morning (7:30-10:30 am) and evening (2:30-5.30 pm). OPLS-DA successfully discriminated the A. paniculata crude extracts into groups of which the main constituents - andrographolide and neoandrographolide - could be mainly observed in the morning session of 120 DAT for P and T, while H gave the highest intensities of these constituents at 150 DAT. The information extracted from ATR-FTIR data through OPLS-DA could be useful in tailoring this plant harvest stage in relation to the content of its two major diterpene lactones: andrographolide and neoandrographolide. © 2014 Society of Chemical Industry.

Effects of hypertonic buffer composition on lymph node uptake and bioavailability of rituximab, after subcutaneous administration.

PubMed

Fathallah, Anas M; Turner, Michael R; Mager, Donald E; Balu-Iyer, Sathy V

2015-03-01

The subcutaneous administration of biologics is highly desirable; however, incomplete bioavailability after s.c. administration remains a major challenge. In this work we investigated the effects of excipient dependent hyperosmolarity on lymphatic uptake and plasma exposure of rituximab as a model protein. Using Swiss Webster (SW) mice as the animal model, we compared the effects of NaCl, mannitol and O-phospho-L-serine (OPLS) on the plasma concentration of rituximab over 5 days after s.c. administration. An increase was observed in plasma concentrations in animals administered rituximab in hypertonic buffer solutions, compared with isotonic buffer. Bioavailability, as estimated by our pharmacokinetic model, increased from 29% in isotonic buffer to 54% in hypertonic buffer containing NaCl, to almost complete bioavailability in hypertonic buffers containing high dose OPLS or mannitol. This improvement in plasma exposure is due to the improved lymphatic trafficking as evident from the increase in the fraction of dose trafficked through the lymph nodes in the presence of hypertonic buffers. The fraction of the dose trafficked through the lymphatics, as estimated by the model, increased from 0.05% in isotonic buffer to 13% in hypertonic buffer containing NaCl to about 30% for hypertonic buffers containing high dose OPLS and mannitol. The data suggest that hypertonic solutions may be a viable option for improving s.c. bioavailability. Copyright © 2014 John Wiley & Sons, Ltd.

Effects of hypertonic buffer composition on lymph node uptake and bioavailability of rituximab, after subcutaneous administration

PubMed Central

Fathallah, Anas M.; Turner, Michael R.; Balu-Iyer, Sathy V.

2015-01-01

Subcutaneous administration of biologics is highly desirable; however, incomplete bioavailability after sc administration remains a major challenge. In this work we investigated the effects of excipient dependent hyper-osmolarity on lymphatic uptake and plasma exposure of rituximab as a model protein. Using Swiss Webster (SW) mice as our animal model, we compared the effects of NaCl, mannitol and, O-Phospho-L-Serine (OPLS) on plasma concentration of rituximab over 5 days after sc administration. We observed an increase in plasma concentrations in animals administered rituximab in hypertonic buffer solutions, as compared to isotonic buffer. Bioavailability, as estimated by our pharmacokinetic model, increased from 29% in isotonic buffer to 54% in hypertonic buffer containing NaCl, to almost complete bioavailability in hypertonic buffers containing high dose OPLS or mannitol. This improvement in plasma exposure is due to improved lymphatic trafficking as evident from the increase in the fraction of dose trafficked through the lymph node in the presence of hypertonic buffers. The fraction of the dose trafficked through the lymphatic, as estimated by the model, increased from 0.05 % in isotonic buffer to 13% in hyper-tonic buffer containing NaCl to about 30% for hypertonic buffers containing high dose OPLS and mannitol. Our data suggests that hypertonic solutions may be a viable option to improve sc bioavailability. PMID:25377184

Raman exfoliative cytology for oral precancer diagnosis

NASA Astrophysics Data System (ADS)

Sahu, Aditi; Gera, Poonam; Pai, Venkatesh; Dubey, Abhishek; Tyagi, Gunjan; Waghmare, Mandavi; Pagare, Sandeep; Mahimkar, Manoj; Murali Krishna, C.

2017-11-01

Oral premalignant lesions (OPLs) such as leukoplakia, erythroplakia, and oral submucous fibrosis, often precede oral cancer. Screening and management of these premalignant conditions can improve prognosis. Raman spectroscopy has previously demonstrated potential in the diagnosis of oral premalignant conditions (in vivo), detected viral infection, and identified cancer in both oral and cervical exfoliated cells (ex vivo). The potential of Raman exfoliative cytology (REC) in identifying premalignant conditions was investigated. Oral exfoliated samples were collected from healthy volunteers (n=20), healthy volunteers with tobacco habits (n=20), and oral premalignant conditions (n=27, OPL) using Cytobrush. Spectra were acquired using Raman microprobe. Spectral acquisition parameters were: λex: 785 nm, laser power: 40 mW, acquisition time: 15 s, and average: 3. Postspectral acquisition, cell pellet was subjected to Pap staining. Multivariate analysis was carried out using principal component analysis and principal component-linear discriminant analysis using both spectra- and patient-wise approaches in three- and two-group models. OPLs could be identified with ˜77% (spectra-wise) and ˜70% (patient-wise) sensitivity in the three-group model while with 86% (spectra-wise) and 83% (patient-wise) in the two-group model. Use of histopathologically confirmed premalignant cases and better sampling devices may help in development of improved standard models and also enhance the sensitivity of the method. Future longitudinal studies can help validate potential of REC in screening and monitoring high-risk populations and prognosis prediction of premalignant lesions.

GC-MS-based metabolite profiling of Cosmos caudatus leaves possessing alpha-glucosidase inhibitory activity.

PubMed

Javadi, Neda; Abas, Faridah; Abd Hamid, Azizah; Simoh, Sanimah; Shaari, Khozirah; Ismail, Intan Safinar; Mediani, Ahmed; Khatib, Alfi

2014-06-01

Cosmos caudatus, which is known as "Ulam Raja," is an herbal plant used in Malaysia to enhance vitality. This study focused on the evaluation of the α-glucosidase inhibitory activity of different ethanolic extracts of C. caudatus. Six series of samples extracted with water, 20%, 40%, 60%, 80%, and 100% ethanol (EtOH) were employed. Gas chromatography-mass spectrometry (GC-MS) and orthogonal partial least-squares (OPLS) analysis was used to correlate bioactivity of different extracts to different metabolite profiles of C. caudatus. The obtained OPLS scores indicated a distinct and remarkable separation into 6 clusters, which were indicative of the 6 different ethanol concentrations. GC-MS can be integrated with multivariate data analysis to identify compounds that inhibit α-glucosidase activity. In addition, catechin, α-linolenic acid, α-D-glucopyranoside, and vitamin E compounds were identified and indicate the potential α-glucosidase inhibitory activity of this herb. GC-MS and multivariate data analysis was applied to discriminate Cosmos caudatus samples extracted with water and different ratio of ethanol. Orthogonal partial least-squares (OPLS) model developed was used to determine the major metabolites contributed to α-glucosidase inhibitory activity. This approach also has the ability to predict the bioactivity of a new set of extracts based on a developed validated regression model that is important for quality control of the herb preparation. © 2014 Institute of Food Technologists®

Evaluating measurement models in clinical research: covariance structure analysis of latent variable models of self-conception.

PubMed

Hoyle, R H

1991-02-01

Indirect measures of psychological constructs are vital to clinical research. On occasion, however, the meaning of indirect measures of psychological constructs is obfuscated by statistical procedures that do not account for the complex relations between items and latent variables and among latent variables. Covariance structure analysis (CSA) is a statistical procedure for testing hypotheses about the relations among items that indirectly measure a psychological construct and relations among psychological constructs. This article introduces clinical researchers to the strengths and limitations of CSA as a statistical procedure for conceiving and testing structural hypotheses that are not tested adequately with other statistical procedures. The article is organized around two empirical examples that illustrate the use of CSA for evaluating measurement models with correlated error terms, higher-order factors, and measured and latent variables.

Latent Heating Structures Derived from TRMM

NASA Technical Reports Server (NTRS)

Tao, W.-K.; Smith, E. A.; Adler, R.; Hou, A.; Kakar, R.; Krishnamurti, T.; Kummerow, C.; Lang, S.; Olson, W.; Satoh, S.

2004-01-01

Rainfall is the fundamental variable within the Earth's hydrological cycle because it is both the main forcing term leading to variations in continental and oceanic surface water budgets. The vertical distribution of latent heat release, which is accompanied with rain, modulates large-scale meridional and zonal circulations within the tropics as well as modifying the energetic efficiency of mid-latitude weather systems. Latent heat release itself is a consequence of phase changes between the vapor, liquid, and frozen states of water.This paper focuses on the retrieval of latent heat release from satellite measurements generated by the Tropical Rainfall Measuring Mission 0. The TRMM observatory, whose development was a joint US-Japan space endeavor, was launched in November 1997. TRMM measurements provide an accurate account of rainfall over the global tropics, information which can be .used to estimate the four-dimensional structure of latent heating across the entire tropical and sub-tropical regions. Various algorithm methodologies for estimating latent heating based on rain rate measurements from TRMM observations are described. The strengths and weaknesses of these algorithms, as well as the latent heating products generated by these algorithms, are also discussed along with validation analyses of the products. The investigation paper provides an overview of how TRMM-derived latent heating information is currently being used in conjunction with global weather and climate models, and concludes with remarks designed to stimulate further research on latent heating retrieval

Parameterization of Ca+2-protein interactions for molecular dynamics simulations.

PubMed

Project, Elad; Nachliel, Esther; Gutman, Menachem

2008-05-01

Molecular dynamics simulations of Ca+2 ions near protein were performed with three force fields: GROMOS96, OPLS-AA, and CHARMM22. The simulations reveal major, force-field dependent, inconsistencies in the interaction between the Ca+2 ions with the protein. The variations are attributed to the nonbonded parameterizations of the Ca+2-carboxylates interactions. The simulations results were compared to experimental data, using the Ca+2-HCOO- equilibrium as a model. The OPLS-AA force field grossly overestimates the binding affinity of the Ca+2 ions to the carboxylate whereas the GROMOS96 and CHARMM22 force fields underestimate the stability of the complex. Optimization of the Lennard-Jones parameters for the Ca+2-carboxylate interactions were carried out, yielding new parameters which reproduce experimental data. Copyright 2007 Wiley Periodicals, Inc.

Investigating the Latent Structure of the Teacher Efficacy Scale

ERIC Educational Resources Information Center

Wagler, Amy; Wagler, Ron

2013-01-01

This article reevaluates the latent structure of the Teacher Efficacy Scale using confirmatory factor analyses (CFAs) on a sample of preservice teachers from a public university in the U.S. Southwest. The fit of a proposed two-factor CFA model with an error correlation structure consistent with internal/ external locus of control is compared to…

A Systematic Approach for Identifying Level-1 Error Covariance Structures in Latent Growth Modeling

ERIC Educational Resources Information Center

Ding, Cherng G.; Jane, Ten-Der; Wu, Chiu-Hui; Lin, Hang-Rung; Shen, Chih-Kang

2017-01-01

It has been pointed out in the literature that misspecification of the level-1 error covariance structure in latent growth modeling (LGM) has detrimental impacts on the inferences about growth parameters. Since correct covariance structure is difficult to specify by theory, the identification needs to rely on a specification search, which,…

Multilevel Higher-Order Item Response Theory Models

ERIC Educational Resources Information Center

Huang, Hung-Yu; Wang, Wen-Chung

2014-01-01

In the social sciences, latent traits often have a hierarchical structure, and data can be sampled from multiple levels. Both hierarchical latent traits and multilevel data can occur simultaneously. In this study, we developed a general class of item response theory models to accommodate both hierarchical latent traits and multilevel data. The…

Nonlinear and Quasi-Simplex Patterns in Latent Growth Models

ERIC Educational Resources Information Center

Bianconcini, Silvia

2012-01-01

In the SEM literature, simplex and latent growth models have always been considered competing approaches for the analysis of longitudinal data, even if they are strongly connected and both of specific importance. General dynamic models, which simultaneously estimate autoregressive structures and latent curves, have been recently proposed in the…

Confidence Intervals for a Semiparametric Approach to Modeling Nonlinear Relations among Latent Variables

ERIC Educational Resources Information Center

Pek, Jolynn; Losardo, Diane; Bauer, Daniel J.

2011-01-01

Compared to parametric models, nonparametric and semiparametric approaches to modeling nonlinearity between latent variables have the advantage of recovering global relationships of unknown functional form. Bauer (2005) proposed an indirect application of finite mixtures of structural equation models where latent components are estimated in the…

Estimating Latent Variable Interactions with Nonnormal Observed Data: A Comparison of Four Approaches

ERIC Educational Resources Information Center

Cham, Heining; West, Stephen G.; Ma, Yue; Aiken, Leona S.

2012-01-01

A Monte Carlo simulation was conducted to investigate the robustness of 4 latent variable interaction modeling approaches (Constrained Product Indicator [CPI], Generalized Appended Product Indicator [GAPI], Unconstrained Product Indicator [UPI], and Latent Moderated Structural Equations [LMS]) under high degrees of nonnormality of the observed…

The Impact of Noninvariant Intercepts in Latent Means Models

ERIC Educational Resources Information Center

Whittaker, Tiffany A.

2013-01-01

Latent means methods such as multiple-indicator multiple-cause (MIMIC) and structured means modeling (SMM) allow researchers to determine whether or not a significant difference exists between groups' factor means. Strong invariance is typically recommended when interpreting latent mean differences. The extent of the impact of noninvariant…

Dynamic Latent Trait Models with Mixed Hidden Markov Structure for Mixed Longitudinal Outcomes.

PubMed

Zhang, Yue; Berhane, Kiros

2016-01-01

We propose a general Bayesian joint modeling approach to model mixed longitudinal outcomes from the exponential family for taking into account any differential misclassification that may exist among categorical outcomes. Under this framework, outcomes observed without measurement error are related to latent trait variables through generalized linear mixed effect models. The misclassified outcomes are related to the latent class variables, which represent unobserved real states, using mixed hidden Markov models (MHMM). In addition to enabling the estimation of parameters in prevalence, transition and misclassification probabilities, MHMMs capture cluster level heterogeneity. A transition modeling structure allows the latent trait and latent class variables to depend on observed predictors at the same time period and also on latent trait and latent class variables at previous time periods for each individual. Simulation studies are conducted to make comparisons with traditional models in order to illustrate the gains from the proposed approach. The new approach is applied to data from the Southern California Children Health Study (CHS) to jointly model questionnaire based asthma state and multiple lung function measurements in order to gain better insight about the underlying biological mechanism that governs the inter-relationship between asthma state and lung function development.

Selection of latent variables for multiple mixed-outcome models

PubMed Central

ZHOU, LING; LIN, HUAZHEN; SONG, XINYUAN; LI, YI

2014-01-01

Latent variable models have been widely used for modeling the dependence structure of multiple outcomes data. However, the formulation of a latent variable model is often unknown a priori, the misspecification will distort the dependence structure and lead to unreliable model inference. Moreover, multiple outcomes with varying types present enormous analytical challenges. In this paper, we present a class of general latent variable models that can accommodate mixed types of outcomes. We propose a novel selection approach that simultaneously selects latent variables and estimates parameters. We show that the proposed estimator is consistent, asymptotically normal and has the oracle property. The practical utility of the methods is confirmed via simulations as well as an application to the analysis of the World Values Survey, a global research project that explores peoples’ values and beliefs and the social and personal characteristics that might influence them. PMID:27642219

pmx: Automated protein structure and topology generation for alchemical perturbations

PubMed Central

Gapsys, Vytautas; Michielssens, Servaas; Seeliger, Daniel; de Groot, Bert L

2015-01-01

Computational protein design requires methods to accurately estimate free energy changes in protein stability or binding upon an amino acid mutation. From the different approaches available, molecular dynamics-based alchemical free energy calculations are unique in their accuracy and solid theoretical basis. The challenge in using these methods lies in the need to generate hybrid structures and topologies representing two physical states of a system. A custom made hybrid topology may prove useful for a particular mutation of interest, however, a high throughput mutation analysis calls for a more general approach. In this work, we present an automated procedure to generate hybrid structures and topologies for the amino acid mutations in all commonly used force fields. The described software is compatible with the Gromacs simulation package. The mutation libraries are readily supported for five force fields, namely Amber99SB, Amber99SB*-ILDN, OPLS-AA/L, Charmm22*, and Charmm36. PMID:25487359

Etiological Beliefs, Treatments, Stigmatizing Attitudes toward Schizophrenia. What Do Italians and Israelis Think?

PubMed

Mannarini, Stefania; Boffo, Marilisa; Rossi, Alessandro; Balottin, Laura

2017-01-01

Background: Although scientific research on the etiology of mental disorders has improved the knowledge of biogenetic and psychosocial aspects related to the onset of mental illness, stigmatizing attitudes and behaviors are still very prevalent and pose a significant social problem. Aim: The aim of this study was to deepen the knowledge of how attitudes toward people with mental illness are affected by specific personal beliefs and characteristics, such as culture and religion of the perceiver. More precisely, the main purpose is the definition of a structure of variables, namely perceived dangerousness, social closeness, and avoidance of the ill person, together with the beliefs about the best treatment to be undertaken and the sick person' gender, capable of describing the complexity of the stigma construct in particular as far as schizophrenia is concerned. Method: The study involved 305 university students, 183 from the University of Padua, Italy, and 122 from the University of Haifa, Israel. For the analyses, a latent class analysis (LCA) approach was chosen to identify a latent categorical structure accounting for the covariance between the observed variables. Such a latent structure was expected to be moderated by cultural background (Italy versus Israel) and religious beliefs, whereas causal beliefs, recommended treatment, dangerousness, social closeness, and public avoidance were the manifest variables, namely the observed indicators of the latent variable. Results: Two sets of results were obtained. First, the relevance of the manifest variables as indicators of the hypothesized latent variable was highlighted. Second, a two-latent-class categorical dimension represented by prejudicial attitudes, causal beliefs, and treatments concerning schizophrenia was found. Specifically, the differential effects of the two cultures and the religious beliefs on the latent structure and their relations highlighted the relevance of the observed variables as indicators of the expected latent variable. Conclusion: The present study contributes to the improvement of the understanding of how attitudes toward people with mental illness are affected by specific personal beliefs and characteristics of the perceiver. The definition of a structure of variables capable of describing the complexity of the stigma construct in particular as far as schizophrenia is concerned was achieved from a cross-cultural perspective.

Potential of mean force analysis of the self-association of leucine-rich transmembrane α-helices: difference between atomistic and coarse-grained simulations.

PubMed

Nishizawa, Manami; Nishizawa, Kazuhisa

2014-08-21

Interaction of transmembrane (TM) proteins is important in many biological processes. Large-scale computational studies using coarse-grained (CG) simulations are becoming popular. However, most CG model parameters have not fully been calibrated with respect to lateral interactions of TM peptide segments. Here, we compare the potential of mean forces (PMFs) of dimerization of TM helices obtained using a MARTINI CG model and an atomistic (AT) Berger lipids-OPLS/AA model (AT(OPLS)). For helical, tryptophan-flanked, leucine-rich peptides (WL15 and WALP15) embedded in a parallel configuration in an octane slab, the AT(OPLS) PMF profiles showed a shallow minimum (with a depth of approximately 3 kJ/mol; i.e., a weak tendency to dimerize). A similar analysis using the CHARMM36 all-atom model (AT(CHARMM)) showed comparable results. In contrast, the CG analysis generally showed steep PMF curves with depths of approximately 16-22 kJ/mol, suggesting a stronger tendency to dimerize compared to the AT model. This CG > AT discrepancy in the propensity for dimerization was also seen for dilauroylphosphatidylcholine (DLPC)-embedded peptides. For a WL15 (and WALP15)/DLPC bilayer system, AT(OPLS) PMF showed a repulsive mean force for a wide range of interhelical distances, in contrast to the attractive forces observed in the octane system. The change from the octane slab to the DLPC bilayer also mitigated the dimerization propensity in the CG system. The dimerization energies of CG (AALALAA)3 peptides in DLPC and dioleoylphosphatidylcholine bilayers were in good agreement with previous experimental data. The lipid headgroup, but not the length of the lipid tails, was a key causative factor contributing to the differences between octane and DLPC. Furthermore, the CG model, but not the AT model, showed high sensitivity to changes in amino acid residues located near the lipid-water interface and hydrophobic mismatch between the peptides and membrane. These findings may help interpret CG and AT simulation results on membrane proteins.

The use of exploration 3D seismic data to optimise oil exploration in OPL 210 deepwater, Nigeria

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

Nelson, L.C.; Lilletveit, R.; Sandvoll, T.

1995-08-01

Allied Energy and the Statoil and BP Alliance are currently partners in the OPL 210 license, in deepwater Nigeria. The license has a 5 year initial exploration phase which carries a two well commitment. To optimize the location of these wells in this challenging and costly drilling environment the partnership has decided to acquire extensive exploration 3D seismic data within the block. Interpretation of the first of two planned 3D surveys has led to a much clearer understanding of: (a) The structural segmentation of the prospect and thus a clearer idea of the likely hydrocarbon pool size. (b) The distributionmore » of amplitude anomalies and thus, hopefully, a superior understanding of reservoir distribution and hydrocarbons. Here the limiting factor is clearly the lack of deepwater geophysical calibration, due to the absence of wells. Consequently, conclusions at this stage, are qualitative either than quantative. Combined with detailed seismic stratigraphic and high tech geophysical analysis, these two aspects will assist in the highgrading of segments in the prospect, prior to final decisions on the well locations. The first well, planned for 1995, will be one of the first wells drilled in the Nigerian deepwater area. Examples of both 2D and 3D data will be used to demonstrate the above and some of the first well results will be integrated into our interpretation to highlight how some of our perceptions may have changed.« less

Maximum Likelihood Estimation of Nonlinear Structural Equation Models with Ignorable Missing Data

ERIC Educational Resources Information Center

Lee, Sik-Yum; Song, Xin-Yuan; Lee, John C. K.

2003-01-01

The existing maximum likelihood theory and its computer software in structural equation modeling are established on the basis of linear relationships among latent variables with fully observed data. However, in social and behavioral sciences, nonlinear relationships among the latent variables are important for establishing more meaningful models…

A Model of Young Children's Social Cognition: Linkages Between Latent Structures and Discrete Processing

ERIC Educational Resources Information Center

Meece, Darrell

1999-01-01

This study proposes a model of associations between young children's social cognition and their social behavior with peers. In this model, two latent structures -children's representations of peer relationships and emotion regulation -- predict children's competent, prosocial, withdrawn, and aggressive behavior. Moreover, the model proposes that…

The Latent Structure of Secure Base Script Knowledge

ERIC Educational Resources Information Center

Waters, Theodore E. A.; Fraley, R. Chris; Groh, Ashley M.; Steele, Ryan D.; Vaughn, Brian E.; Bost, Kelly K.; Veríssimo, Manuela; Coppola, Gabrielle; Roisman, Glenn I.

2015-01-01

There is increasing evidence that attachment representations abstracted from childhood experiences with primary caregivers are organized as a cognitive script describing secure base use and support (i.e., the "secure base script"). To date, however, the latent structure of secure base script knowledge has gone unexamined--this despite…

Serum metabolomics strategy for understanding pharmacological effects of ShenQi pill acting on kidney yang deficiency syndrome.

PubMed

Nan, Yang; Zhou, Xiaohang; Liu, Qi; Zhang, Aihua; Guan, Yu; Lin, Shanhua; Kong, Ling; Han, Ying; Wang, Xijun

2016-07-15

Kidney yang deficiency syndrome, a diagnostic pattern in Chinese medicine, is similar with clinical features of the glucocorticoid withdrawal syndrome. The aim of this present study was to explore low molecular mass differentiating metabolites between control group and model group of kidney yang deficiency rats induced with corticosterone as well as the therapeutic effect of Shen Qi Pill, a classic traditional Chinese medicine formula for treating Kidney yang deficiency syndrome in China. This study utilized ultra-performance liquid chromatography coupled with electrospray ionization synapt quadrupole time-of-flight high definition mass spectrometry (UPLC/ESI-SYNAPT-QTOF-HDMS) to identify the underlying biomarkers for clarifying mechanism of Shen Qi Pill in treating Kidney yang deficiency syndrome based on metabolite profiling of the serum samples and in conjunction with multivariate and pathway analysis. Meanwhile, blood biochemistry assay and histopathology were examined to identify specific changes in the model group rats. Distinct changes in the pattern of metabolites were observed by UPLC-HDMS. The changes in metabolic profiling were restored to their baseline values after treatment with Shen Qi Pill according to the combined with a principal component analysis (PCA) score plots. Altogether, the current metabolomics approach based on UPLC-HDMS and orthogonal projection to latent structures discriminate analysis (OPLS-DA) demonstrated 27 ions (18 in the negative mode, 9 in the positive mode, 17 ions restored by Shen Qi Pill). These results indicated that effectiveness of Shen Qi Pill in Kidney yang deficiency syndrome rats induced a substantial change in the metabolic profiles by regulating the biomarkers and adjusting the metabolic disorder. It suggested that the metabolomics approach was a powerful approach for elucidation of pathologic changes of Chinese medicine syndrome and action mechanisms of traditional Chinese medicine. Copyright © 2015 Elsevier B.V. All rights reserved.

Targeted Metabolomics Approach To Detect the Misuse of Steroidal Aromatase Inhibitors in Equine Sports by Biomarker Profiling.

PubMed

Chan, George Ho Man; Ho, Emmie Ngai Man; Leung, David Kwan Kon; Wong, Kin Sing; Wan, Terence See Ming

2016-01-05

The use of anabolic androgenic steroids (AAS) is prohibited in both human and equine sports. The conventional approach in doping control testing for AAS (as well as other prohibited substances) is accomplished by the direct detection of target AAS or their characteristic metabolites in biological samples using hyphenated techniques such as gas chromatography or liquid chromatography coupled with mass spectrometry. Such an approach, however, falls short when dealing with unknown designer steroids where reference materials and their pharmacokinetics are not available. In addition, AASs with fast elimination times render the direct detection approach ineffective as the detection window is short. A targeted metabolomics approach is a plausible alternative to the conventional direct detection approach for controlling the misuse of AAS in sports. Because the administration of AAS of the same class may trigger similar physiological responses or effects in the body, it may be possible to detect such administrations by monitoring changes in the endogenous steroidal expression profile. This study attempts to evaluate the viability of using the targeted metabolomics approach to detect the administration of steroidal aromatase inhibitors, namely androst-4-ene-3,6,17-trione (6-OXO) and androsta-1,4,6-triene-3,17-dione (ATD), in horses. Total (free and conjugated) urinary concentrations of 31 endogenous steroids were determined by gas chromatography-tandem mass spectrometry for a group of 2 resting and 2 in-training thoroughbred geldings treated with either 6-OXO or ATD. Similar data were also obtained from a control (untreated) group of in-training thoroughbred geldings (n = 28). Statistical processing and chemometric procedures using principle component analysis and orthogonal projection to latent structures-discriminant analysis (OPLS-DA) have highlighted 7 potential biomarkers that could be used to differentiate urine samples obtained from the control and the treated groups. On the basis of this targeted metabolomic approach, the administration of 6-OXO and ATD could be detected for much longer relative to that of the conventional direct detection approach.

Effects of long term supplementation of anabolic androgen steroids on human skeletal muscle.

PubMed

Yu, Ji-Guo; Bonnerud, Patrik; Eriksson, Anders; Stål, Per S; Tegner, Yelverton; Malm, Christer

2014-01-01

The effects of long-term (over several years) anabolic androgen steroids (AAS) administration on human skeletal muscle are still unclear. In this study, seventeen strength training athletes were recruited and individually interviewed regarding self-administration of banned substances. Ten subjects admitted having taken AAS or AAS derivatives for the past 5 to 15 years (Doped) and the dosage and type of banned substances were recorded. The remaining seven subjects testified to having never used any banned substances (Clean). For all subjects, maximal muscle strength and body composition were tested, and biopsies from the vastus lateralis muscle were obtained. Using histochemistry and immunohistochemistry (IHC), muscle biopsies were evaluated for morphology including fiber type composition, fiber size, capillary variables and myonuclei. Compared with the Clean athletes, the Doped athletes had significantly higher lean leg mass, capillary per fibre and myonuclei per fiber. In contrast, the Doped athletes had significantly lower absolute value in maximal squat force and relative values in maximal squat force (relative to lean body mass, to lean leg mass and to muscle fiber area). Using multivariate statistics, an orthogonal projection of latent structure discriminant analysis (OPLS-DA) model was established, in which the maximal squat force relative to muscle mass and the maximal squat force relative to fiber area, together with capillary density and nuclei density were the most important variables for separating Doped from the Clean athletes (regression  =  0.93 and prediction  =  0.92, p<0.0001). In Doped athletes, AAS dose-dependent increases were observed in lean body mass, muscle fiber area, capillary density and myonuclei density. In conclusion, long term AAS supplementation led to increases in lean leg mass, muscle fiber size and a parallel improvement in muscle strength, and all were dose-dependent. Administration of AAS may induce sustained morphological changes in human skeletal muscle, leading to physical performance enhancement.

Effects of Long Term Supplementation of Anabolic Androgen Steroids on Human Skeletal Muscle

PubMed Central

Yu, Ji-Guo; Bonnerud, Patrik; Eriksson, Anders; Stål, Per S.; Tegner, Yelverton; Malm, Christer

2014-01-01

The effects of long-term (over several years) anabolic androgen steroids (AAS) administration on human skeletal muscle are still unclear. In this study, seventeen strength training athletes were recruited and individually interviewed regarding self-administration of banned substances. Ten subjects admitted having taken AAS or AAS derivatives for the past 5 to 15 years (Doped) and the dosage and type of banned substances were recorded. The remaining seven subjects testified to having never used any banned substances (Clean). For all subjects, maximal muscle strength and body composition were tested, and biopsies from the vastus lateralis muscle were obtained. Using histochemistry and immunohistochemistry (IHC), muscle biopsies were evaluated for morphology including fiber type composition, fiber size, capillary variables and myonuclei. Compared with the Clean athletes, the Doped athletes had significantly higher lean leg mass, capillary per fibre and myonuclei per fiber. In contrast, the Doped athletes had significantly lower absolute value in maximal squat force and relative values in maximal squat force (relative to lean body mass, to lean leg mass and to muscle fiber area). Using multivariate statistics, an orthogonal projection of latent structure discriminant analysis (OPLS-DA) model was established, in which the maximal squat force relative to muscle mass and the maximal squat force relative to fiber area, together with capillary density and nuclei density were the most important variables for separating Doped from the Clean athletes (regression  =  0.93 and prediction  =  0.92, p<0.0001). In Doped athletes, AAS dose-dependent increases were observed in lean body mass, muscle fiber area, capillary density and myonuclei density. In conclusion, long term AAS supplementation led to increases in lean leg mass, muscle fiber size and a parallel improvement in muscle strength, and all were dose-dependent. Administration of AAS may induce sustained morphological changes in human skeletal muscle, leading to physical performance enhancement. PMID:25207812

Phenolic Profiling for Traceability of Vanilla ×tahitensis

PubMed Central

Busconi, Matteo; Lucini, Luigi; Soffritti, Giovanna; Bernardi, Jamila; Bernardo, Letizia; Brunschwig, Christel; Lepers-Andrzejewski, Sandra; Raharivelomanana, Phila; Fernandez, Jose A.

2017-01-01

Vanilla is a flavoring recovered from the cured beans of the orchid genus Vanilla. Vanilla ×tahitensis is traditionally cultivated on the islands of French Polynesia, where vanilla vines were first introduced during the nineteenth century and, since the 1960s, have been introduced to other Pacific countries such as Papua New Guinea (PNG), cultivated and sold as “Tahitian vanilla,” although both sensory properties and aspect are different. From an economic point of view, it is important to ensure V. ×tahitensis traceability and to guarantee that the marketed product is part of the future protected designation of the origin “Tahitian vanilla” (PDO), currently in progress in French Polynesia. The application of metabolomics, allowing the detection and simultaneous analysis of hundreds or thousands of metabolites from different matrices, has recently gained high interest in food traceability. Here, metabolomics analysis of phenolic compounds profiles was successfully applied for the first time to V. ×tahitensis to deepen our knowledge of vanilla metabolome, focusing on phenolics compounds, for traceability purposes. Phenolics were screened through a quadrupole-time-of-flight mass spectrometer coupled to a UHPLC liquid chromatography system, and 260 different compounds were clearly evidenced and subjected to different statistical analysis in order to enable the discrimination of the samples based on their origin. Eighty-eight and twenty three compounds, with a prevalence of flavonoids, resulted to be highly discriminant through ANOVA and Orthogonal Projections to Latent Structures Discriminant Analysis (OPLS-DA) respectively. Volcano plot analysis and pairwise comparisons were carried out to determine those compounds, mainly responsible for the differences among samples as a consequence of either origin or cultivar. The samples from PNG were clearly different from the Tahitian samples that were further divided in two different groups based on the different phenolic patterns. Among the 260 compounds, metabolomics analysis enabled the detection of previously unreported phenolics in vanilla (such as flavonoids, lignans, stilbenes and other polyphenols). PMID:29075276

Phenolic Profiling for Traceability of Vanilla ×tahitensis.

PubMed

Busconi, Matteo; Lucini, Luigi; Soffritti, Giovanna; Bernardi, Jamila; Bernardo, Letizia; Brunschwig, Christel; Lepers-Andrzejewski, Sandra; Raharivelomanana, Phila; Fernandez, Jose A

2017-01-01

Vanilla is a flavoring recovered from the cured beans of the orchid genus Vanilla . Vanilla × tahitensis is traditionally cultivated on the islands of French Polynesia, where vanilla vines were first introduced during the nineteenth century and, since the 1960s, have been introduced to other Pacific countries such as Papua New Guinea (PNG), cultivated and sold as "Tahitian vanilla," although both sensory properties and aspect are different. From an economic point of view, it is important to ensure V . × tahitensis traceability and to guarantee that the marketed product is part of the future protected designation of the origin "Tahitian vanilla" (PDO), currently in progress in French Polynesia. The application of metabolomics, allowing the detection and simultaneous analysis of hundreds or thousands of metabolites from different matrices, has recently gained high interest in food traceability. Here, metabolomics analysis of phenolic compounds profiles was successfully applied for the first time to V . × tahitensis to deepen our knowledge of vanilla metabolome, focusing on phenolics compounds, for traceability purposes. Phenolics were screened through a quadrupole-time-of-flight mass spectrometer coupled to a UHPLC liquid chromatography system, and 260 different compounds were clearly evidenced and subjected to different statistical analysis in order to enable the discrimination of the samples based on their origin. Eighty-eight and twenty three compounds, with a prevalence of flavonoids, resulted to be highly discriminant through ANOVA and Orthogonal Projections to Latent Structures Discriminant Analysis (OPLS-DA) respectively. Volcano plot analysis and pairwise comparisons were carried out to determine those compounds, mainly responsible for the differences among samples as a consequence of either origin or cultivar. The samples from PNG were clearly different from the Tahitian samples that were further divided in two different groups based on the different phenolic patterns. Among the 260 compounds, metabolomics analysis enabled the detection of previously unreported phenolics in vanilla (such as flavonoids, lignans, stilbenes and other polyphenols).

¹H NMR-based metabolic profiling of human rectal cancer tissue

PubMed Central

2013-01-01

Background Rectal cancer is one of the most prevalent tumor types. Understanding the metabolic profile of rectal cancer is important for developing therapeutic approaches and molecular diagnosis. Methods Here, we report a metabonomics profiling of tissue samples on a large cohort of human rectal cancer subjects (n = 127) and normal controls (n = 43) using 1H nuclear magnetic resonance (1H NMR) based metabonomics assay, which is a highly sensitive and non-destructive method for the biomarker identification in biological systems. Principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA) and orthogonal projection to latent structure with discriminant analysis (OPLS-DA) were applied to analyze the 1H-NMR profiling data to identify the distinguishing metabolites of rectal cancer. Results Excellent separation was obtained and distinguishing metabolites were observed among the different stages of rectal cancer tissues (stage I = 35; stage II = 37; stage III = 37 and stage IV = 18) and normal controls. A total of 38 differential metabolites were identified, 16 of which were closely correlated with the stage of rectal cancer. The up-regulation of 10 metabolites, including lactate, threonine, acetate, glutathione, uracil, succinate, serine, formate, lysine and tyrosine, were detected in the cancer tissues. On the other hand, 6 metabolites, including myo-inositol, taurine, phosphocreatine, creatine, betaine and dimethylglycine were decreased in cancer tissues. These modified metabolites revealed disturbance of energy, amino acids, ketone body and choline metabolism, which may be correlated with the progression of human rectal cancer. Conclusion Our findings firstly identify the distinguishing metabolites in different stages of rectal cancer tissues, indicating possibility of the attribution of metabolites disturbance to the progression of rectal cancer. The altered metabolites may be as potential biomarkers, which would provide a promising molecular diagnostic approach for clinical diagnosis of human rectal cancer. The role and underlying mechanism of metabolites in rectal cancer progression are worth being further investigated. PMID:24138801

Nonlinear Structured Growth Mixture Models in M"plus" and OpenMx

ERIC Educational Resources Information Center

Grimm, Kevin J.; Ram, Nilam; Estabrook, Ryne

2010-01-01

Growth mixture models (GMMs; B. O. Muthen & Muthen, 2000; B. O. Muthen & Shedden, 1999) are a combination of latent curve models (LCMs) and finite mixture models to examine the existence of latent classes that follow distinct developmental patterns. GMMs are often fit with linear, latent basis, multiphase, or polynomial change models…

Use of Latent Profile Analysis in Studies of Gifted Students

ERIC Educational Resources Information Center

Mammadov, Sakhavat; Ward, Thomas J.; Cross, Jennifer Riedl; Cross, Tracy L.

2016-01-01

To date, in gifted education and related fields various conventional factor analytic and clustering techniques have been used extensively for investigation of the underlying structure of data. Latent profile analysis is a relatively new method in the field. In this article, we provide an introduction to latent profile analysis for gifted education…

Software for the Application of Discrete Latent Structure Models to Item Response Data.

ERIC Educational Resources Information Center

Haertel, Edward H.

These FORTRAN programs and MATHEMATICA routines were developed in the course of a research project titled "Achievement and Assessment in School Science: Modeling and Mapping Ability and Performance." Their use is described in other publications from that project, including "Latent Traits or Latent States? The Role of Discrete Models…

Visualizing Confidence Bands for Semiparametrically Estimated Nonlinear Relations among Latent Variables

ERIC Educational Resources Information Center

Pek, Jolynn; Chalmers, R. Philip; Kok, Bethany E.; Losardo, Diane

2015-01-01

Structural equation mixture models (SEMMs), when applied as a semiparametric model (SPM), can adequately recover potentially nonlinear latent relationships without their specification. This SPM is useful for exploratory analysis when the form of the latent regression is unknown. The purpose of this article is to help users familiar with structural…

Higher-Order Item Response Models for Hierarchical Latent Traits

ERIC Educational Resources Information Center

Huang, Hung-Yu; Wang, Wen-Chung; Chen, Po-Hsi; Su, Chi-Ming

2013-01-01

Many latent traits in the human sciences have a hierarchical structure. This study aimed to develop a new class of higher order item response theory models for hierarchical latent traits that are flexible in accommodating both dichotomous and polytomous items, to estimate both item and person parameters jointly, to allow users to specify…

Space-time latent component modeling of geo-referenced health data.

PubMed

Lawson, Andrew B; Song, Hae-Ryoung; Cai, Bo; Hossain, Md Monir; Huang, Kun

2010-08-30

Latent structure models have been proposed in many applications. For space-time health data it is often important to be able to find the underlying trends in time, which are supported by subsets of small areas. Latent structure modeling is one such approach to this analysis. This paper presents a mixture-based approach that can be applied to component selection. The analysis of a Georgia ambulatory asthma county-level data set is presented and a simulation-based evaluation is made. Copyright (c) 2010 John Wiley & Sons, Ltd.

The effects of rurality on substance use disorder diagnosis: A multiple-groups latent class analysis.

PubMed

Brooks, Billy; McBee, Matthew; Pack, Robert; Alamian, Arsham

2017-05-01

Rates of accidental overdose mortality from substance use disorder (SUD) have risen dramatically in the United States since 1990. Between 1999 and 2004 alone rates increased 62% nationwide, with rural overdose mortality increasing at a rate 3 times that seen in urban populations. Cultural differences between rural and urban populations (e.g., educational attainment, unemployment rates, social characteristics, etc.) affect the nature of SUD, leading to disparate risk of overdose across these communities. Multiple-groups latent class analysis with covariates was applied to data from the 2011 and 2012 National Survey on Drug Use and Health (n=12.140) to examine potential differences in latent classifications of SUD between rural and urban adult (aged 18years and older) populations. Nine drug categories were used to identify latent classes of SUD defined by probability of diagnosis within these categories. Once the class structures were established for rural and urban samples, posterior membership probabilities were entered into a multinomial regression analysis of socio-demographic predictors' association with the likelihood of SUD latent class membership. Latent class structures differed across the sub-groups, with the rural sample fitting a 3-class structure (Bootstrap Likelihood Ratio Test P value=0.03) and the urban fitting a 6-class model (Bootstrap Likelihood Ratio Test P value<0.0001). Overall the rural class structure exhibited less diversity in class structure and lower prevalence of SUD in multiple drug categories (e.g. cocaine, hallucinogens, and stimulants). This result supports the hypothesis that different underlying elements exist in the two populations that affect SUD patterns, and thus can inform the development of surveillance instruments, clinical services, and prevention programming tailored to specific communities. Copyright © 2017 Elsevier Ltd. All rights reserved.

Age-Related Alterations in the Retinal Microvasculature, Microcirculation, and Microstructure.

PubMed

Wei, Yantao; Jiang, Hong; Shi, Yingying; Qu, Dongyi; Gregori, Giovanni; Zheng, Fang; Rundek, Tatjana; Wang, Jianhua

2017-07-01

To characterize age-related alterations in the retinal microcirculation, microvascular network, and microstructure in healthy subjects. Seventy-four healthy subjects aged from 18 to 82 years were recruited and divided into four age groups (G1 with age <35 years, G2 with age 35 ∼ 49 years, G3 with age 50 ∼ 64 years, and G4 with age ≥65 years). Custom ultra-high resolution optical coherence tomography (UHR-OCT) was used to acquire six intraretinal layers of the macula. OCT angiography (OCTA) was used to image the retinal microvascular network. The retinal blood flow velocity (BFV) was measured using a Retinal Function Imager (RFI). Compared to G1, G2 had significant thinning of the retinal nerve fiber layer (RNFL) (P < 0.05), while G3 had thinning of the RNFL and ganglion cell and inner plexiform layer (GCIPL) (P < 0.05), in addition to thickening of the outer plexiform layer (OPL) and photoreceptor layer (PR) (P < 0.05). G4 had loss in retinal vessel density, thinning in RNFL and GCIPL, and decrease in venular BFV, in addition to thickening of the OPL and PR (P < 0.05). Age was negatively related to retinal vessel densities, the inner retinal layers, and venular BFV (P < 0.05). By contrast, age was positively related to OPL and PR (P < 0.05). During aging, decreases in retinal vessel density, inner retinal layer thickness, and venular BFV were evident and impacted each other as observed by simultaneous changes in multiple retinal components.

Database of the United States Coal Pellet Collection of the U.S. Geological Survey Organic Petrology Laboratory

USGS Publications Warehouse

Deems, Nikolaus J.; Hackley, Paul C.

2012-01-01

The Organic Petrology Laboratory (OPL) of the U.S. Geological Survey (USGS) Eastern Energy Resources Science Center in Reston, Virginia, contains several thousand processed coal sample materials that were loosely organized in laboratory drawers for the past several decades. The majority of these were prepared as 1-inch-diameter particulate coal pellets (more than 6,000 pellets; one sample usually was prepared as two pellets, although some samples were prepared in as many as four pellets), which were polished and used in reflected light petrographic studies. These samples represent the work of many scientists from the 1970s to the present, most notably Ron Stanton, who managed the OPL until 2001 (see Warwick and Ruppert, 2005, for a comprehensive bibliography of Ron Stanton's work). The purpose of the project described herein was to organize and catalog the U.S. part of the petrographic sample collection into a comprehensive database (available with this report as a Microsoft Excel file) and to compile and list published studies associated with the various sample sets. Through this work, the extent of the collection is publicly documented as a resource and sample library available to other scientists and researchers working in U.S. coal basins previously studied by organic petrologists affiliated with the USGS. Other researchers may obtain samples in the OPL collection on loan at the discretion of the USGS authors listed in this report and its associated Web page.

Transportable and vibration-free full-field low-coherent quantitative phase microscope

NASA Astrophysics Data System (ADS)

Yamauchi, Toyohiko; Yamada, Hidenao; Goto, Kentaro; Matsui, Hisayuki; Yasuhiko, Osamu; Ueda, Yukio

2018-02-01

We developed a transportable Linnik-type full-field low-coherent quantitative phase microscope that is able to compensate for optical path length (OPL) disturbance due to environmental mechanical noises. Though two-beam interferometers such as Linnik ones suffer from unstable OPL difference, we overcame this problem with a mechanical feedback system based on digital signal-processing that controls the OPL difference in sub-nanometer resolution precisely with a feedback bandwidth of 4 kHz. The developed setup has a footprint of 200 mm by 200 mm, a height of 500 mm, and a weight of 4.5 kilograms. In the transmission imaging mode, cells were cultured on a reflection-enhanced glass-bottom dish, and we obtained interference images sequentially while performing stepwise quarter-wavelength phase-shifting. Real-time image processing, including retrieval of the unwrapped phase from interference images and its background correction, along with the acquisition of interference images, was performed on a laptop computer. Emulation of the phase contrast (PhC) images and the differential interference contrast (DIC) images was also performed in real time. Moreover, our setup was applied for full-field cell membrane imaging in the reflection mode, where the cells were cultured on an anti-reflection (AR)-coated glass-bottom dish. The phase and intensity of the light reflected by the membrane revealed the outer shape of the cells independent of the refractive index. In this paper, we show imaging results on cultured cells in both transmission and reflection modes.

Malingering as a Categorical or Dimensional Construct: The Latent Structure of Feigned Psychopathology as Measured by the SIRS and MMPI-2

ERIC Educational Resources Information Center

Walters, Glenn D.; Rogers, Richard; Berry, David T. R.; Miller, Holly A.; Duncan, Scott A.; McCusker, Paul J.; Payne, Joshua W.; Granacher, Robert P., Jr.

2008-01-01

The 6 nonoverlapping primary scales of the Structured Interview of Reported Symptoms (SIRS) were subjected to taxometric analysis in a group of 1,211 criminal and civil examinees in order to investigate the latent structure of feigned psychopathology. Both taxometric procedures used in this study, mean above minus below a cut (MAMBAC) and maximum…

Unconstrained Structural Equation Models of Latent Interactions: Contrasting Residual- and Mean-Centered Approaches

ERIC Educational Resources Information Center

Marsh, Herbert W.; Wen, Zhonglin; Hau, Kit-Tai; Little, Todd D.; Bovaird, James A.; Widaman, Keith F.

2007-01-01

Little, Bovaird and Widaman (2006) proposed an unconstrained approach with residual centering for estimating latent interaction effects as an alternative to the mean-centered approach proposed by Marsh, Wen, and Hau (2004, 2006). Little et al. also differed from Marsh et al. in the number of indicators used to infer the latent interaction factor…

Using Structural Equation Models with Latent Variables to Study Student Growth and Development.

ERIC Educational Resources Information Center

Pike, Gary R.

1991-01-01

Analysis of data on freshman-to-senior developmental gains in 722 University of Tennessee-Knoxville students provides evidence of the advantages of structural equation modeling with latent variables and suggests that the group differences identified by traditional analysis of variance and covariance techniques may be an artifact of measurement…

A Taxometric Study of the Latent Structure of Disgust Sensitivity: Converging Evidence for Dimensionality

ERIC Educational Resources Information Center

Olatunji, Bunmi O.; Broman-Fulks, Joshua J.

2007-01-01

Disgust sensitivity has recently been implicated as a specific vulnerability factor for several anxiety-related disorders. However, it is not clear whether disgust sensitivity is a dimensional or categorical phenomenon. The present study examined the latent structure of disgust by applying three taxometric procedures (maximum eigenvalue, mean…

Some Factor Analytic Approximations to Latent Class Structure.

ERIC Educational Resources Information Center

Dziuban, Charles D.; Denton, William T.

Three procedures, alpha, image, and uniqueness rescaling, were applied to a joint occurrence probability matrix. That matrix was the basis of a well-known latent class structure. The values of the recurring subscript elements were varied as follows: Case 1 - The known elements were input; Case 2 - The upper bounds to the recurring subscript…

The Latent Structure of Psychopathy in Youth: A Taxometric Investigation

ERIC Educational Resources Information Center

Vasey, Michael W.; Kotov, Roman; Frick, Paul J.; Loney, Bryan R.

2005-01-01

Using taxometric procedures, the latent structure of psychopathy was investigated in two studies of children and adolescents. Prior studies have identified a taxon (i.e., a natural category) associated with antisocial behavior in adults as well as children and adolescents. However, features of this taxon suggest that it is not psychopathy but…

Heterogeneity in the Latent Structure of PTSD Symptoms among Canadian Veterans

ERIC Educational Resources Information Center

Naifeh, James A.; Richardson, J. Don; Del Ben, Kevin S.; Elhai, Jon D.

2010-01-01

The current study used factor mixture modeling to identify heterogeneity (i.e., latent classes) in 2 well-supported models of posttraumatic stress disorder's (PTSD) factor structure. Data were analyzed from a clinical sample of 405 Canadian veterans evaluated for PTSD. Results were consistent with our hypotheses. Each PTSD factor model was best…

Dual role for the latent transforming growth factor-beta binding protein in storage of latent TGF-beta in the extracellular matrix and as a structural matrix protein

PubMed Central

1995-01-01

The role of the latent TGF-beta binding protein (LTBP) is unclear. In cultures of fetal rat calvarial cells, which form mineralized bonelike nodules, both LTBP and the TGF-beta 1 precursor localized to large fibrillar structures in the extracellular matrix. The appearance of these fibrillar structures preceded the appearance of type I collagen fibers. Plasmin treatment abolished the fibrillar staining pattern for LTBP and released a complex containing both LTBP and TGF-beta. Antibodies and antisense oligonucleotides against LTBP inhibited the formation of mineralized bonelike nodules in long-term fetal rat calvarial cultures. Immunohistochemistry of fetal and adult rat bone confirmed a fibrillar staining pattern for LTBP in vivo. These findings, together with the known homology of LTBP to the fibrillin family of proteins, suggest a novel function for LTBP, in addition to its role in matrix storage of latent TGF-beta, as a structural matrix protein that may play a role in bone formation. PMID:7593177

DelPhi Web Server: A comprehensive online suite for electrostatic calculations of biological macromolecules and their complexes

PubMed Central

Sarkar, Subhra; Witham, Shawn; Zhang, Jie; Zhenirovskyy, Maxim; Rocchia, Walter; Alexov, Emil

2011-01-01

Here we report a web server, the DelPhi web server, which utilizes DelPhi program to calculate electrostatic energies and the corresponding electrostatic potential and ionic distributions, and dielectric map. The server provides extra services to fix structural defects, as missing atoms in the structural file and allows for generation of missing hydrogen atoms. The hydrogen placement and the corresponding DelPhi calculations can be done with user selected force field parameters being either Charmm22, Amber98 or OPLS. Upon completion of the calculations, the user is given option to download fixed and protonated structural file, together with the parameter and Delphi output files for further analysis. Utilizing Jmol viewer, the user can see the corresponding structural file, to manipulate it and to change the presentation. In addition, if the potential map is requested to be calculated, the potential can be mapped onto the molecule surface. The DelPhi web server is available from http://compbio.clemson.edu/delphi_webserver. PMID:24683424

Vertical Profiles of Latent Heat Release Over the Global Tropics using TRMM Rainfall Products from December 1997 to November 2001

NASA Technical Reports Server (NTRS)

Tao, W.-K.; Lang, S.; Simpson, J.; Meneghini, R.; Halverson, J.; Johnson, R.; Adler, R.; Starr, David (Technical Monitor)

2002-01-01

NASA Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) derived rainfall information will be used to estimate the four-dimensional structure of global monthly latent heating and rainfall profiles over the global tropics from December 1997 to November 2000. Rainfall, latent heating and radar reflectivity structures between El Nino (DJF 1997-98) and La Nina (DJF 1998-99) will be examined and compared. The seasonal variation of heating over various geographic locations (i.e., oceanic vs continental, Indian ocean vs west Pacific, Africa vs S. America) will also be analyzed. In addition, the relationship between rainfall, latent heating (maximum heating level), radar reflectivity and SST is examined and will be presented in the meeting. The impact of random error and bias in stratiform percentage estimates from PR on latent heating profiles is studied and will also be presented in the meeting. Additional information is included in the original extended abstract.

Building Coherent Validation Arguments for the Measurement of Latent Constructs with Unified Statistical Frameworks

ERIC Educational Resources Information Center

Rupp, Andre A.

2012-01-01

In the focus article of this issue, von Davier, Naemi, and Roberts essentially coupled: (1) a short methodological review of structural similarities of latent variable models with discrete and continuous latent variables; and (2) 2 short empirical case studies that show how these models can be applied to real, rather than simulated, large-scale…

The Longitudinal Structure of General and Specific Anxiety Dimensions in Children: Testing a Latent Trait-State-Occasion Model

ERIC Educational Resources Information Center

Olatunji, Bunmi O.; Cole, David A.

2009-01-01

In an 8-wave, 4-year longitudinal study, 787 children (Grades 3-6) completed the Revised Children's Manifest Anxiety Scale (C. R. Reynolds & B. O. Richmond, 1985), a measure of the Physiological Reactivity, Worry-Oversensitivity, and Social Alienation dimensions of anxiety. A latent variable (trait-state-occasion) model and a latent growth curve…

Sex Differences in Latent Cognitive Abilities Ages 6 to 59: Evidence from the Woodcock-Johnson III Tests of Cognitive Abilities

ERIC Educational Resources Information Center

Keith, Timothy Z.; Reynolds, Matthew R.; Patel, Puja G.; Ridley, Kristen P.

2008-01-01

Sex differences in the latent general and broad cognitive abilities underlying the Woodcock-Johnson Tests of Cognitive Abilities were investigated for children, youth, and adults ages 6 through 59. A developmental, multiple indicator-multiple cause, structural equation model was used to investigate sex differences in latent cognitive abilities as…

Sex Differences in Latent Cognitive Abilities Ages 5 to 17: Evidence from the Differential Ability Scales--Second Edition

ERIC Educational Resources Information Center

Keith, Timothy Z.; Reynolds, Matthew R.; Roberts, Lisa G.; Winter, Amanda L.; Austin, Cynthia A.

2011-01-01

Sex differences in the latent general and broad cognitive abilities underlying the Differential Ability Scales, Second Edition were investigated for children and youth ages 5 through 17. Multi-group mean and covariance structural equation modeling was used to investigate sex differences in latent cognitive abilities as well as changes in these…

An Assessment of Character and Leadership Development Latent Factor Structures through Confirmatory Factor, Item Response Theory, and Latent Class Analyses

ERIC Educational Resources Information Center

Higginbotham, David L.

2013-01-01

This study leveraged the complementary nature of confirmatory factor (CFA), item response theory (IRT), and latent class (LCA) analyses to strengthen the rigor and sophistication of evaluation of two new measures of the Air Force Academy's "leader of character" definition--the Character Mosaic Virtues (CMV) and the Leadership Mosaic…

The Log-Linear Cognitive Diagnostic Model (LCDM) as a Special Case of The General Diagnostic Model (GDM). Research Report. ETS RR-14-40

ERIC Educational Resources Information Center

von Davier, Matthias

2014-01-01

Diagnostic models combine multiple binary latent variables in an attempt to produce a latent structure that provides more information about test takers' performance than do unidimensional latent variable models. Recent developments in diagnostic modeling emphasize the possibility that multiple skills may interact in a conjunctive way within the…

Precipitation Processes Derived from TRMM Satellite Data, Cloud Resolving Model and Field Campaigns

NASA Technical Reports Server (NTRS)

Tao, W.-K.; Lang, S.; Simpson, J.; Meneghini, R.; Halverson, J.; Johnson, R.; Adler, R.; Einaudi, Franco (Technical Monitor)

2001-01-01

Rainfall is a key link in the hydrologic cycle and is a primary heat source for the atmosphere. The vertical distribution of latent-heat release, which is accompanied by rainfall, modulates the large-scale circulations of the tropics and in turn can impact midlatitude weather. This latent heat release is a consequence of phase changes between vapor, liquid. and solid water. Present large-scale weather and climate models can simulate cloud latent heat release only crudely thus reducing their confidence in predictions on both global and regional scales. In this paper, NASA Tropical Rainfall Measuring (TRMM) precipitation radar (PR) derived rainfall information and the Goddard Convective and Stratiform Heating (CSH) algorithm used to estimate the four-dimensional structure of global monthly latent heating and rainfall profiles over the global tropics from December 1997 to October 2000. Rainfall latent heating and radar reflectively structure between ENSO (1997-1998 winter) and non-ENSO (1998-1999 winter) periods are examined and compared. The seasonal variation of heating over various geographic locations (i.e. Indian ocean vs west Pacific; Africa vs S. America) are also analyzed. In addition, the relationship between rainfall latent heating maximum heating level), radar reflectively and SST are examined.

Modeling Latent Interactions at Level 2 in Multilevel Structural Equation Models: An Evaluation of Mean-Centered and Residual-Centered Unconstrained Approaches

ERIC Educational Resources Information Center

Leite, Walter L.; Zuo, Youzhen

2011-01-01

Among the many methods currently available for estimating latent variable interactions, the unconstrained approach is attractive to applied researchers because of its relatively easy implementation with any structural equation modeling (SEM) software. Using a Monte Carlo simulation study, we extended and evaluated the unconstrained approach to…

Standard Errors of Estimated Latent Variable Scores with Estimated Structural Parameters

ERIC Educational Resources Information Center

Hoshino, Takahiro; Shigemasu, Kazuo

2008-01-01

The authors propose a concise formula to evaluate the standard error of the estimated latent variable score when the true values of the structural parameters are not known and must be estimated. The formula can be applied to factor scores in factor analysis or ability parameters in item response theory, without bootstrap or Markov chain Monte…

Taxometric and Factor Analytic Models of Anxiety Sensitivity among Youth: Exploring the Latent Structure of Anxiety Psychopathology Vulnerability

ERIC Educational Resources Information Center

Bernstein, Amit; Zvolensky, Michael J.; Stewart, Sherry; Comeau, Nancy

2007-01-01

This study represents an effort to better understand the latent structure of anxiety sensitivity (AS), a well-established affect-sensitivity individual difference factor, among youth by employing taxometric and factor analytic approaches in an integrative manner. Taxometric analyses indicated that AS, as indexed by the Child Anxiety Sensitivity…

Structural Relationships between Social Activities and Longitudinal Trajectories of Depression among Older Adults

ERIC Educational Resources Information Center

Hong, Song-Iee; Hasche, Leslie; Bowland, Sharon

2009-01-01

Purpose: This study examines the structural relationships between social activities and trajectories of late-life depression. Design and Methods: Latent class analysis was used with a nationally representative sample of older adults (N = 5,294) from the Longitudinal Study on Aging II to classify patterns of social activities. A latent growth curve…

Factor Structure Invariance of the Kaufman Adolescent and Adult Intelligence Test across Male and Female Samples

ERIC Educational Resources Information Center

Immekus, Jason C.; Maller, Susan J.

2010-01-01

Multisample confirmatory factor analysis (MCFA) and latent mean structures analysis (LMS) were used to test measurement invariance and latent mean differences on the Kaufman Adolescent and Adult Intelligence Scale[TM] (KAIT) across males and females in the standardization sample. MCFA found that the parameters of the KAIT two-factor model were…

Introduction to the special section on mixture modeling in personality assessment.

PubMed

Wright, Aidan G C; Hallquist, Michael N

2014-01-01

Latent variable models offer a conceptual and statistical framework for evaluating the underlying structure of psychological constructs, including personality and psychopathology. Complex structures that combine or compare categorical and dimensional latent variables can be accommodated using mixture modeling approaches, which provide a powerful framework for testing nuanced theories about psychological structure. This special series includes introductory primers on cross-sectional and longitudinal mixture modeling, in addition to empirical examples applying these techniques to real-world data collected in clinical settings. This group of articles is designed to introduce personality assessment scientists and practitioners to a general latent variable framework that we hope will stimulate new research and application of mixture models to the assessment of personality and its pathology.

Application of Generative Autoencoder in De Novo Molecular Design.

PubMed

Blaschke, Thomas; Olivecrona, Marcus; Engkvist, Ola; Bajorath, Jürgen; Chen, Hongming

2018-01-01

A major challenge in computational chemistry is the generation of novel molecular structures with desirable pharmacological and physiochemical properties. In this work, we investigate the potential use of autoencoder, a deep learning methodology, for de novo molecular design. Various generative autoencoders were used to map molecule structures into a continuous latent space and vice versa and their performance as structure generator was assessed. Our results show that the latent space preserves chemical similarity principle and thus can be used for the generation of analogue structures. Furthermore, the latent space created by autoencoders were searched systematically to generate novel compounds with predicted activity against dopamine receptor type 2 and compounds similar to known active compounds not included in the trainings set were identified. © 2018 The Authors. Published by Wiley-VCH Verlag GmbH & Co. KGaA.

Developing model asphalt systems using molecular simulation : final model.

DOT National Transportation Integrated Search

2009-09-01

Computer based molecular simulations have been used towards developing simple mixture compositions whose : physical properties resemble those of real asphalts. First, Monte Carlo simulations with the OPLS all-atom force : field were used to predict t...

LigParGen web server: an automatic OPLS-AA parameter generator for organic ligands

PubMed Central

Dodda, Leela S.

2017-01-01

Abstract The accurate calculation of protein/nucleic acid–ligand interactions or condensed phase properties by force field-based methods require a precise description of the energetics of intermolecular interactions. Despite the progress made in force fields, small molecule parameterization remains an open problem due to the magnitude of the chemical space; the most critical issue is the estimation of a balanced set of atomic charges with the ability to reproduce experimental properties. The LigParGen web server provides an intuitive interface for generating OPLS-AA/1.14*CM1A(-LBCC) force field parameters for organic ligands, in the formats of commonly used molecular dynamics and Monte Carlo simulation packages. This server has high value for researchers interested in studying any phenomena based on intermolecular interactions with ligands via molecular mechanics simulations. It is free and open to all at jorgensenresearch.com/ligpargen, and has no login requirements. PMID:28444340

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

Nam, Y. B., E-mail: southub@postech.ac.kr; Yun, G. S.; Lee, D. J.

Electron cyclotron emission imaging (ECEI) diagnostic on Korean Superconducting Tokamak Advanced Research utilizes quasi-optical heterodyne-detection method to measure 2D (vertical and radial) T{sub e} fluctuations from two toroidally separated poloidal cross section of the plasma. A cylindrical lens local oscillator (LO) optics with optical path length (OPL) 2–2.5 m has been used in the current ECEI system to couple the LO source to the 24 vertically aligned array of ECE detectors. For efficient and compact LO optics employing the Powell lens is proposed so that the OPL of the LO source is significantly reduced from ∼2.0 m to 0.4 mmore » with new optics. The coupling efficiency of the LO source is expected to be improved especially at the edge channels. Results from the optical simulation together with the laboratory test of the prototype optics will be discussed in this paper.« less

Design of near-infrared dyes for nonlinear optics: toward optical limiting applications at telecommunication wavelengths

NASA Astrophysics Data System (ADS)

Bellier, Quentin; Bouit, Pierre-Antoine; Kamada, Kenji; Feneyrou, Patrick; Malmström, E.; Maury, Olivier; Andraud, Chantal

2009-09-01

The rapid development of frequency-tunable pulsed lasers up to telecommunication wavelengths (1400-1600 nm) led to the design of new materials for nonlinear absorption in this spectral range. In this context, two families of near infra-red (NIR) chromophores, namely heptamethine cyanine and aza-borondipyrromethene (aza-bodipy) dyes were studied. In both cases, they show significant two-photon absorption (TPA) cross-sections in the 1400-1600 nm spectral range and display good optical power limiting (OPL) properties. OPL curves were interpreted on the basis of TPA followed by excited state absorption (ESA) phenomena. Finally these systems have several relevant properties like nonlinear absorption properties, gram scale synthesis and high solubility. In addition, they could be functionalized on several sites which open the way to numerous practical applications in biology, solid-state optical limiting and signal processing.

Metabolomics study of Populus type propolis.

PubMed

Anđelković, Boban; Vujisić, Ljubodrag; Vučković, Ivan; Tešević, Vele; Vajs, Vlatka; Gođevac, Dejan

2017-02-20

Herein, we propose rapid and simple spectroscopic methods to determine the chemical composition of propolis derived from various Populus species using a metabolomics approach. In order to correlate variability in Populus type propolis composition with the altitude of its collection, NMR, IR, and UV spectroscopy followed by OPLS was conducted. The botanical origin of propolis was established by comparing propolis spectral data to those of buds of various Populus species. An O2PLS method was utilized to integrate two blocks of data. According to OPLS and O2PLS, the major compounds in propolis samples, collected from temperate continental climate above 500m, were phenolic glycerides originating from P. tremula buds. Flavonoids were predominant in propolis samples collected below 400m, originating from P. nigra and P. x euramericana buds. Samples collected at 400-500m were of mixed origin, with variable amounts of all detected metabolites. Copyright © 2016 Elsevier B.V. All rights reserved.

Research on the application of a decoupling algorithm for structure analysis

NASA Technical Reports Server (NTRS)

Denman, E. D.

1980-01-01

The mathematical theory for decoupling mth-order matrix differential equations is presented. It is shown that the decoupling precedure can be developed from the algebraic theory of matrix polynomials. The role of eigenprojectors and latent projectors in the decoupling process is discussed and the mathematical relationships between eigenvalues, eigenvectors, latent roots, and latent vectors are developed. It is shown that the eigenvectors of the companion form of a matrix contains the latent vectors as a subset. The spectral decomposition of a matrix and the application to differential equations is given.

A Retrieval of Tropical Latent Heating Using the 3D Structure of Precipitation Features

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

Ahmed, Fiaz; Schumacher, Courtney; Feng, Zhe

Traditionally, radar-based latent heating retrievals use rainfall to estimate the total column-integrated latent heating and then distribute that heating in the vertical using a model-based look-up table (LUT). In this study, we develop a new method that uses size characteristics of radar-observed precipitating echo (i.e., area and mean echo-top height) to estimate the vertical structure of latent heating. This technique (named the Convective-Stratiform Area [CSA] algorithm) builds on the fact that the shape and magnitude of latent heating profiles are dependent on the organization of convective systems and aims to avoid some of the pitfalls involved in retrieving accurate rainfallmore » amounts and microphysical information from radars and models. The CSA LUTs are based on a high-resolution Weather Research and Forecasting model (WRF) simulation whose domain spans much of the near-equatorial Indian Ocean. When applied to S-PolKa radar observations collected during the DYNAMO/CINDY2011/AMIE field campaign, the CSA retrieval compares well to heating profiles from a sounding-based budget analysis and improves upon a simple rain-based latent heating retrieval. The CSA LUTs also highlight the fact that convective latent heating increases in magnitude and height as cluster area and echo-top heights grow, with a notable congestus signature of cooling at mid levels. Stratiform latent heating is less dependent on echo-top height, but is strongly linked to area. Unrealistic latent heating profiles in the stratiform LUT, viz., a low-level heating spike, an elevated melting layer, and net column cooling were identified and corrected for. These issues highlight the need for improvement in model parameterizations, particularly in linking microphysical phase changes to larger mesoscale processes.« less

Assessing a dysphoric arousal model of acute stress disorder symptoms in a clinical sample of rape and bank robbery victims

PubMed Central

Hansen, Maj; Armour, Cherie; Elklit, Ask

2012-01-01

Background Since the introduction of Acute Stress Disorder (ASD) into the 4th edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV) research has focused on the ability of ASD to predict PTSD rather than focusing on addressing ASD's underlying latent structure. The few existing confirmatory factor analytic (CFA) studies of ASD have failed to reach a clear consensus regarding ASD's underlying dimensionality. Although, the discrepancy in the results may be due to varying ASD prevalence rates, it remains possible that the model capturing the latent structure of ASD has not yet been put forward. One such model may be a replication of a new five-factor model of PTSD, which separates the arousal symptom cluster into Dysphoric and Anxious Arousal. Given the pending DSM-5, uncovering ASD's latent structure is more pertinent than ever. Objective Using CFA, four different models of the latent structure of ASD were specified and tested: the proposed DSM-5 model, the DSM-IV model, a three factor model, and a five factor model separating the arousal symptom cluster. Method The analyses were based on a combined sample of rape and bank robbery victims, who all met the diagnostic criteria for ASD (N = 404) using the Acute Stress Disorder Scale. Results The results showed that the five factor model provided the best fit to the data. Conclusions The results of the present study suggest that the dimensionality of ASD may be best characterized as a five factor structure which separates dysphoric and anxious arousal items into two separate factors, akin to recent research on PTSD's latent structure. Thus, the current study adds to the debate about how ASD should be conceptualized in the pending DSM-5. PMID:22893845

Assessing a dysphoric arousal model of acute stress disorder symptoms in a clinical sample of rape and bank robbery victims.

PubMed

Hansen, Maj; Armour, Cherie; Elklit, Ask

2012-01-01

Since the introduction of Acute Stress Disorder (ASD) into the 4th edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV) research has focused on the ability of ASD to predict PTSD rather than focusing on addressing ASD's underlying latent structure. The few existing confirmatory factor analytic (CFA) studies of ASD have failed to reach a clear consensus regarding ASD's underlying dimensionality. Although, the discrepancy in the results may be due to varying ASD prevalence rates, it remains possible that the model capturing the latent structure of ASD has not yet been put forward. One such model may be a replication of a new five-factor model of PTSD, which separates the arousal symptom cluster into Dysphoric and Anxious Arousal. Given the pending DSM-5, uncovering ASD's latent structure is more pertinent than ever. USING CFA, FOUR DIFFERENT MODELS OF THE LATENT STRUCTURE OF ASD WERE SPECIFIED AND TESTED: the proposed DSM-5 model, the DSM-IV model, a three factor model, and a five factor model separating the arousal symptom cluster. The analyses were based on a combined sample of rape and bank robbery victims, who all met the diagnostic criteria for ASD (N = 404) using the Acute Stress Disorder Scale. The results showed that the five factor model provided the best fit to the data. The results of the present study suggest that the dimensionality of ASD may be best characterized as a five factor structure which separates dysphoric and anxious arousal items into two separate factors, akin to recent research on PTSD's latent structure. Thus, the current study adds to the debate about how ASD should be conceptualized in the pending DSM-5.

Application of Phase Shifted, Laser Feedback Interferometry to Fluid Physics

NASA Technical Reports Server (NTRS)

Ovryn, Ben; Eppell, Steven J.; Andrews, James H.; Khaydarov, John

1996-01-01

We have combined the principles of phase-shifting interferometry (PSI) and laser-feedback interferometry (LFI) to produce a new instrument that can measure both optical path length (OPL) changes and discern sample reflectivity variations. In LFI, coherent feedback of the incident light either reflected directly from a surface or reflected after transmission through a region of interest will modulate the output intensity of the laser. LFI can yield a high signal-to-noise ratio even for low reflectivity samples. By combining PSI and LFI, we have produced a robust instrument, based upon a HeNe laser, with high dynamic range that can be used to measure either static (dc) or oscillatory changes along the optical path. As with other forms of interferometry, large changes in OPL require phase unwrapping. Conversely, small phase changes are limited by the fraction of a fringe that can be measured. We introduce the phase shifts with an electro-optic modulator (EOM) and use either the Carre or Hariharan algorithms to determine the phase and visibility. We have determined the accuracy and precision of our technique by measuring both the bending of a cantilevered piezoelectric bimorph and linear ramps to the EOM. Using PSI, sub-nanometer displacements can be measured. We have combined our interferometer with a commercial microscope and scanning piezoelectric stage and have measured the variation in OPL and visibility for drops of PDMS (silicone oil) on coated single crystal silicon. Our measurement of the static contact angle agrees with the value of 68 deg stated in the literature.

Age-Related Alterations in the Retinal Microvasculature, Microcirculation, and Microstructure

PubMed Central

Wei, Yantao; Jiang, Hong; Shi, Yingying; Qu, Dongyi; Gregori, Giovanni; Zheng, Fang; Rundek, Tatjana; Wang, Jianhua

2017-01-01

Purpose To characterize age-related alterations in the retinal microcirculation, microvascular network, and microstructure in healthy subjects. Methods Seventy-four healthy subjects aged from 18 to 82 years were recruited and divided into four age groups (G1 with age <35 years, G2 with age 35 ∼ 49 years, G3 with age 50 ∼ 64 years, and G4 with age ≥65 years). Custom ultra-high resolution optical coherence tomography (UHR-OCT) was used to acquire six intraretinal layers of the macula. OCT angiography (OCTA) was used to image the retinal microvascular network. The retinal blood flow velocity (BFV) was measured using a Retinal Function Imager (RFI). Results Compared to G1, G2 had significant thinning of the retinal nerve fiber layer (RNFL) (P < 0.05), while G3 had thinning of the RNFL and ganglion cell and inner plexiform layer (GCIPL) (P < 0.05), in addition to thickening of the outer plexiform layer (OPL) and photoreceptor layer (PR) (P < 0.05). G4 had loss in retinal vessel density, thinning in RNFL and GCIPL, and decrease in venular BFV, in addition to thickening of the OPL and PR (P < 0.05). Age was negatively related to retinal vessel densities, the inner retinal layers, and venular BFV (P < 0.05). By contrast, age was positively related to OPL and PR (P < 0.05). Conclusions During aging, decreases in retinal vessel density, inner retinal layer thickness, and venular BFV were evident and impacted each other as observed by simultaneous changes in multiple retinal components. PMID:28744554

Gene Expression Profiling Predicts the Development of Oral Cancer

PubMed Central

Saintigny, Pierre; Zhang, Li; Fan, You-Hong; El-Naggar, Adel K.; Papadimitrakopoulou, Vali; Feng, Lei; Lee, J. Jack; Kim, Edward S.; Hong, Waun Ki; Mao, Li

2011-01-01

Patients with oral preneoplastic lesion (OPL) have high risk of developing oral cancer. Although certain risk factors such as smoking status and histology are known, our ability to predict oral cancer risk remains poor. The study objective was to determine the value of gene expression profiling in predicting oral cancer development. Gene expression profile was measured in 86 of 162 OPL patients who were enrolled in a clinical chemoprevention trial that used the incidence of oral cancer development as a prespecified endpoint. The median follow-up time was 6.08 years and 35 of the 86 patients developed oral cancer over the course. Gene expression profiles were associated with oral cancer-free survival and used to develope multivariate predictive models for oral cancer prediction. We developed a 29-transcript predictive model which showed marked improvement in terms of prediction accuracy (with 8% predicting error rate) over the models using previously known clinico-pathological risk factors. Based on the gene expression profile data, we also identified 2182 transcripts significantly associated with oral cancer risk associated genes (P-value<0.01, single variate Cox proportional hazards model). Functional pathway analysis revealed proteasome machinery, MYC, and ribosomes components as the top gene sets associated with oral cancer risk. In multiple independent datasets, the expression profiles of the genes can differentiate head and neck cancer from normal mucosa. Our results show that gene expression profiles may improve the prediction of oral cancer risk in OPL patients and the significant genes identified may serve as potential targets for oral cancer chemoprevention. PMID:21292635

Gene features selection for three-class disease classification via multiple orthogonal partial least square discriminant analysis and S-plot using microarray data.

PubMed

Yang, Mingxing; Li, Xiumin; Li, Zhibin; Ou, Zhimin; Liu, Ming; Liu, Suhuan; Li, Xuejun; Yang, Shuyu

2013-01-01

DNA microarray analysis is characterized by obtaining a large number of gene variables from a small number of observations. Cluster analysis is widely used to analyze DNA microarray data to make classification and diagnosis of disease. Because there are so many irrelevant and insignificant genes in a dataset, a feature selection approach must be employed in data analysis. The performance of cluster analysis of this high-throughput data depends on whether the feature selection approach chooses the most relevant genes associated with disease classes. Here we proposed a new method using multiple Orthogonal Partial Least Squares-Discriminant Analysis (mOPLS-DA) models and S-plots to select the most relevant genes to conduct three-class disease classification and prediction. We tested our method using Golub's leukemia microarray data. For three classes with subtypes, we proposed hierarchical orthogonal partial least squares-discriminant analysis (OPLS-DA) models and S-plots to select features for two main classes and their subtypes. For three classes in parallel, we employed three OPLS-DA models and S-plots to choose marker genes for each class. The power of feature selection to classify and predict three-class disease was evaluated using cluster analysis. Further, the general performance of our method was tested using four public datasets and compared with those of four other feature selection methods. The results revealed that our method effectively selected the most relevant features for disease classification and prediction, and its performance was better than that of the other methods.

The Use of a Context-Based Information Retrieval Technique

DTIC Science & Technology

2009-07-01

provided in context. Latent Semantic Analysis (LSA) is a statistical technique for inferring contextual and structural information, and previous studies...WAIS). 10 DSTO-TR-2322 1.4.4 Latent Semantic Analysis LSA, which is also known as latent semantic indexing (LSI), uses a statistical and...1.4.6 Language Models In contrast, natural language models apply algorithms that combine statistical information with semantic information. Semantic

Latent factor structure of a behavioral economic marijuana demand curve.

PubMed

Aston, Elizabeth R; Farris, Samantha G; MacKillop, James; Metrik, Jane

2017-08-01

Drug demand, or relative value, can be assessed via analysis of behavioral economic purchase task performance. Five demand indices are typically obtained from drug purchase tasks. The goal of this research was to determine whether metrics of marijuana reinforcement from a marijuana purchase task (MPT) exhibit a latent factor structure that efficiently characterizes marijuana demand. Participants were regular marijuana users (n = 99; 37.4% female, 71.5% marijuana use days [5 days/week], 15.2% cannabis dependent) who completed study assessments, including the MPT, during a baseline session. Principal component analysis was used to examine the latent structure underlying MPT indices. Concurrent validity was assessed via examination of relationships between latent factors and marijuana use, past quit attempts, and marijuana expectancies. A two-factor solution was confirmed as the best fitting structure, accounting for 88.5% of the overall variance. Factor 1 (65.8% variance) reflected "Persistence," indicating sensitivity to escalating marijuana price, which comprised four MPT indices (elasticity, O max , P max , and breakpoint). Factor 2 (22.7% variance) reflected "Amplitude," indicating the amount consumed at unrestricted price (intensity). Persistence factor scores were associated with fewer past marijuana quit attempts and lower expectancies of negative use outcomes. Amplitude factor scores were associated with more frequent use, dependence symptoms, craving severity, and positive marijuana outcome expectancies. Consistent with research on alcohol and cigarette purchase tasks, the MPT can be characterized with a latent two-factor structure. Thus, demand for marijuana appears to encompass distinct dimensions of price sensitivity and volumetric consumption, with differential relations to other aspects of marijuana motivation.

Students' Views on Mathematics in Single-Sex and Coed Classrooms in Ghana

ERIC Educational Resources Information Center

Bofah, Emmanuel Adu-tutu; Hannula, Markku S.

2016-01-01

In this study, we investigated students' views on themselves as learners of mathematics as a function of school-by-sex (N = 2034, MAge = 18.49, SDAge = 1.25; 12th-grade; 58.2% girls). Using latent variable Structural Equation Modeling (SEM), the measurement and structural equivalence as well as the equality of latent means of scores across…

The Information a Test Provides on an Ability Parameter. Research Report. ETS RR-07-18

ERIC Educational Resources Information Center

Haberman, Shelby J.

2007-01-01

In item-response theory, if a latent-structure model has an ability variable, then elementary information theory may be employed to provide a criterion for evaluation of the information the test provides concerning ability. This criterion may be considered even in cases in which the latent-structure model is not valid, although interpretation of…

The NEO Five-Factor Inventory: Latent Structure and Relationships with Dimensions of Anxiety and Depressive Disorders in a Large Clinical Sample

ERIC Educational Resources Information Center

Rosellini, Anthony J.; Brown, Timothy A.

2011-01-01

The present study evaluated the latent structure of the NEO Five-Factor Inventory (NEO FFI) and relations between the five-factor model (FFM) of personality and dimensions of "DSM-IV" anxiety and depressive disorders (panic disorder, generalized anxiety disorder [GAD], obsessive-compulsive disorder, social phobia [SOC], major depressive disorder…

Taxometric and Factor Analytic Models of Anxiety Sensitivity: Integrating Approaches to Latent Structural Research

ERIC Educational Resources Information Center

Bernstein, Amit; Zvolensky, Michael J.; Norton, Peter J.; Schmidt, Norman B.; Taylor, Steven; Forsyth, John P.; Lewis, Sarah F.; Feldner, Matthew T.; Leen-Feldner, Ellen W.; Stewart, Sherry H.; Cox, Brian

2007-01-01

This study represents an effort to better understand the latent structure of anxiety sensitivity (AS), as indexed by the 16-item Anxiety Sensitivity Index (ASI; S. Reiss, R. A. Peterson, M. Gursky, & R. J. McNally, 1986), by using taxometric and factor-analytic approaches in an integrative manner. Taxometric analyses indicated that AS has a…

Association between pathology and texture features of multi parametric MRI of the prostate

NASA Astrophysics Data System (ADS)

Kuess, Peter; Andrzejewski, Piotr; Nilsson, David; Georg, Petra; Knoth, Johannes; Susani, Martin; Trygg, Johan; Helbich, Thomas H.; Polanec, Stephan H.; Georg, Dietmar; Nyholm, Tufve

2017-10-01

The role of multi-parametric (mp)MRI in the diagnosis and treatment of prostate cancer has increased considerably. An alternative to visual inspection of mpMRI is the evaluation using histogram-based (first order statistics) parameters and textural features (second order statistics). The aims of the present work were to investigate the relationship between benign and malignant sub-volumes of the prostate and textures obtained from mpMR images. The performance of tumor prediction was investigated based on the combination of histogram-based and textural parameters. Subsequently, the relative importance of mpMR images was assessed and the benefit of additional imaging analyzed. Finally, sub-structures based on the PI-RADS classification were investigated as potential regions to automatically detect maligned lesions. Twenty-five patients who received mpMRI prior to radical prostatectomy were included in the study. The imaging protocol included T2, DWI, and DCE. Delineation of tumor regions was performed based on pathological information. First and second order statistics were derived from each structure and for all image modalities. The resulting data were processed with multivariate analysis, using PCA (principal component analysis) and OPLS-DA (orthogonal partial least squares discriminant analysis) for separation of malignant and healthy tissue. PCA showed a clear difference between tumor and healthy regions in the peripheral zone for all investigated images. The predictive ability of the OPLS-DA models increased for all image modalities when first and second order statistics were combined. The predictive value reached a plateau after adding ADC and T2, and did not increase further with the addition of other image information. The present study indicates a distinct difference in the signatures between malign and benign prostate tissue. This is an absolute prerequisite for automatic tumor segmentation, but only the first step in that direction. For the specific identified signature, DCE did not add complementary information to T2 and ADC maps.

Using Instrumental Variable (IV) Tests to Evaluate Model Specification in Latent Variable Structural Equation Models*

PubMed Central

Kirby, James B.; Bollen, Kenneth A.

2009-01-01

Structural Equation Modeling with latent variables (SEM) is a powerful tool for social and behavioral scientists, combining many of the strengths of psychometrics and econometrics into a single framework. The most common estimator for SEM is the full-information maximum likelihood estimator (ML), but there is continuing interest in limited information estimators because of their distributional robustness and their greater resistance to structural specification errors. However, the literature discussing model fit for limited information estimators for latent variable models is sparse compared to that for full information estimators. We address this shortcoming by providing several specification tests based on the 2SLS estimator for latent variable structural equation models developed by Bollen (1996). We explain how these tests can be used to not only identify a misspecified model, but to help diagnose the source of misspecification within a model. We present and discuss results from a Monte Carlo experiment designed to evaluate the finite sample properties of these tests. Our findings suggest that the 2SLS tests successfully identify most misspecified models, even those with modest misspecification, and that they provide researchers with information that can help diagnose the source of misspecification. PMID:20419054

Post-traumatic stress symptoms and structure among orphan and vulnerable children and adolescents in Zambia.

PubMed

Familiar, Itziar; Murray, Laura; Gross, Alden; Skavenski, Stephanie; Jere, Elizabeth; Bass, Judith

2014-11-01

Scant information exists on PTSD symptoms and structure in youth from developing countries. We describe the symptom profile and exposure to trauma experiences among 343 orphan and vulnerable children and adolescents from Zambia. We distinguished profiles of post-traumatic stress symptoms using latent class analysis. Average number of trauma-related symptoms (21.6; range 0-38) was similar across sex and age. Latent class model suggested 3 classes varying by level of severity: low (31% of the sample), medium (45% of the sample), and high (24% of the sample) symptomatology. Results suggest that PTSD is a continuously distributed latent trait.

Application of core-shell-structured CdTe@SiO2 quantum dots synthesized via a facile solution method for improving latent fingerprint detection

NASA Astrophysics Data System (ADS)

Gao, Feng; Han, Jiaxing; Lv, Caifeng; Wang, Qin; Zhang, Jun; Li, Qun; Bao, Liru; Li, Xin

2012-10-01

Fingerprint detection is important in criminal investigation. This paper reports a facile powder brushing technique for improving latent fingerprint detection using core-shell-structured CdTe@SiO2 quantum dots (QDs) as fluorescent labeling marks. Core-shell-structured CdTe@SiO2 QDs are prepared via a simple solution-based approach using NH2NH2·H2O as pH adjustor and stabilizer, and their application for improving latent fingerprint detection is explored. The obtained CdTe@SiO2 QDs show spherical shapes with well-defined core-shell structures encapsulating different amounts of QDs depending on the type of the pH adjustor and stabilizer. Moreover, the fluorescence of CdTe@SiO2 QDs is largely enhanced by surface modification of the SiO2 shell. The CdTe@SiO2 QDs overcome the oxidation problem of pure CdTe QDs in air, thus affording better variability with strong adhesive ability, better resolution, and bright emission colors for practical application in latent fingerprint detection. In comparison with the conventional fluorescence powders, silver powders, and others, the effectiveness of CdTe@SiO2 QD powders for detection of latent fingerprints present on a large variety of object surfaces is greatly improved. The synthesis method for CdTe@SiO2 QDs is simple, cheap, and easy for large-scale production, and thus offers many advantages in the practical application of fingerprint detection.

A taxometric investigation of agoraphobia in a clinical and a community sample.

PubMed

Slade, Tim; Grisham, Jessica R

2009-08-01

The nosological status of agoraphobia is controversial. Agoraphobia may be a distinct diagnostic entity or a marker of avoidance severity. The current study examines the latent structure of agoraphobia through the use of taxometric analysis. The latent structure of agoraphobia was examined in two independent samples, one comprising outpatients presenting for treatment for panic disorder (PD) with or without agoraphobia (n=365), and the other comprising community volunteers to a national mental health survey who experienced fear or avoidance of at least one prototypic agoraphobic situation (n=640). Two taxometric procedures were carried out - maximum eigenvalue (MAXEIG) and mean above minus below a cut (MAMBAC) - using indicators derived from questionnaire measures of, and structured diagnostic interviews for, agoraphobia. Results show consistent evidence of dimensional latent structure in both samples. It is concluded that scores on measures of agoraphobia best represent an agoraphobic severity dimension.

Nucleotide sequence and proposed secondary structure of Columnea latent viroid: a natural mosaic of viroid sequences.

PubMed Central

Hammond, R; Smith, D R; Diener, T O

1989-01-01

The Columnea latent viroid (CLV) occurs latently in certain Columnea erythrophae plants grown commercially. In potato and tomato, CLV causes potato spindle tuber viroid (PSTV)-like symptoms. Its nucleotide sequence and proposed secondary structure reveal that CLV consists of a single-stranded circular RNA of 370 nucleotides which can assume a rod-like structure with extensive base-pairing characteristic of all known viroids. The electrophoretic mobility of circular CLV under nondenaturing conditions suggests a potential tertiary structure. CLV contains extensive sequence homologies to the PSTV group of viroids but contains a central conserved region identical to that of hop stunt viroid (HSV). CLV also shares some biological properties with each of the two types of viroids. Most probably, CLV is the result of intracellular RNA recombination between an HSV-type and one or more PSTV-type viroids replicating in the same plant. Images PMID:2602114

Robust Measurement via A Fused Latent and Graphical Item Response Theory Model.

PubMed

Chen, Yunxiao; Li, Xiaoou; Liu, Jingchen; Ying, Zhiliang

2018-03-12

Item response theory (IRT) plays an important role in psychological and educational measurement. Unlike the classical testing theory, IRT models aggregate the item level information, yielding more accurate measurements. Most IRT models assume local independence, an assumption not likely to be satisfied in practice, especially when the number of items is large. Results in the literature and simulation studies in this paper reveal that misspecifying the local independence assumption may result in inaccurate measurements and differential item functioning. To provide more robust measurements, we propose an integrated approach by adding a graphical component to a multidimensional IRT model that can offset the effect of unknown local dependence. The new model contains a confirmatory latent variable component, which measures the targeted latent traits, and a graphical component, which captures the local dependence. An efficient proximal algorithm is proposed for the parameter estimation and structure learning of the local dependence. This approach can substantially improve the measurement, given no prior information on the local dependence structure. The model can be applied to measure both a unidimensional latent trait and multidimensional latent traits.

Latent constructs of the autobiographical memory questionnaire: a recollection-belief model of autobiographical experience.

PubMed

Fitzgerald, Joseph M; Broadbridge, Carissa L

2013-01-01

Many researchers employ single-item scales of subjective experiences such as imagery and confidence to assess autobiographical memory. We tested the hypothesis that four latent constructs, recollection, belief, impact, and rehearsal, account for the variance in commonly used scales across four different types of autobiographical memory: earliest childhood memory, cue word memory of personal experience, highly vivid memory, and most stressful memory. Participants rated each memory on scales hypothesised to be indicators of one of four latent constructs. Multi-group confirmatory factor analyses and structural analyses confirmed the similarity of the latent constructs of recollection, belief, impact, and rehearsal, as well as the similarity of the structural relationships among those constructs across memory type. The observed pattern of mean differences between the varieties of autobiographical experiences was consistent with prior research and theory in the study of autobiographical memory.

Environmental risk perception, environmental concern and propensity to participate in organic farming programmes.

PubMed

Toma, Luiza; Mathijs, Erik

2007-04-01

This paper aims to identify the factors underlying farmers' propensity to participate in organic farming programmes in a Romanian rural region that confronts non-point source pollution. For this, we employ structural equation modelling with latent variables using a specific data set collected through an agri-environmental farm survey in 2001. The model includes one 'behavioural intention' latent variable ('propensity to participate in organic farming programmes') and five 'attitude' and 'socio-economic' latent variables ('socio-demographic characteristics', 'economic characteristics', 'agri-environmental information access', 'environmental risk perception' and 'general environmental concern'). The results indicate that, overall, the model has an adequate fit to the data. All loadings are statistically significant, supporting the theoretical basis for assignment of indicators for each latent variable. The significance tests for the structural model parameters show 'environmental risk perception' as the strongest determinant of farmers' propensity to participate in organic farming programmes.

Evaluating the Latent Structure of the MMPI-2 F(p) Scale in a Forensic Sample: A Taxometric Analysis

ERIC Educational Resources Information Center

Strong, David R.; Glassmire, David M.; Frederick, Richard I.; Greene, Roger L.

2006-01-01

P. A. Arbisi and Y. S. Ben-Porath (1995) originally proposed that the Infrequency Psychopathology scale, F(p), be used as the final step in an algorithm to determine the validity of a Minnesota Multiphasic Personality Inventory-2 (MMPI-2) protocol. The current study used taxometric procedures to determine the latent structure of F(p) among…

Modeling Latent Growth Curves With Incomplete Data Using Different Types of Structural Equation Modeling and Multilevel Software

ERIC Educational Resources Information Center

Ferrer, Emilio; Hamagami, Fumiaki; McArdle, John J.

2004-01-01

This article offers different examples of how to fit latent growth curve (LGC) models to longitudinal data using a variety of different software programs (i.e., LISREL, Mx, Mplus, AMOS, SAS). The article shows how the same model can be fitted using both structural equation modeling and multilevel software, with nearly identical results, even in…

The Latent Structures of the Learning and Study Strategies Inventory (LASSI): A Comparative Analysis.

ERIC Educational Resources Information Center

Obiekwe, Jerry C.

The first purpose of this study was to analyze the results of the confirmatory factor analyses, via EQS, with regard to the latent structures of the Learning and Study Strategies Inventory (LASSI) (C. Weinstein, D. Palmer, and A. Schulte, 1987) as proposed by S. Olejnik and S. Nist (1992), A. Olivarez and M. Tallent-Runnels (1994), B. Olaussen and…

A Taxometric Investigation of the Latent Structure of Worry: Dimensionality and Associations with Depression, Anxiety, and Stress

ERIC Educational Resources Information Center

Olatunji, Bunmi O.; Broman-Fulks, Joshua J.; Bergman, Shawn M.; Green, Bradley A.; Zlomke, Kimberly R.

2010-01-01

Worry has been described as a core feature of several disorders, particularly generalized anxiety disorder (GAD). The present study examined the latent structure of worry by applying 3 taxometric procedures (MAXEIG, MAMBAC, and L-Mode) to data collected from 2 large samples. Worry in the first sample (Study 1) of community participants (n = 1,355)…

Optical properties of drug metabolites in latent fingermarks

PubMed Central

Shen, Yao; Ai, Qing

2016-01-01

Drug metabolites usually have structures of split-ring resonators (SRRs), which might lead to negative permittivity and permeability in electromagnetic field. As a result, in the UV-vis region, the latent fingermarks images of drug addicts and non drug users are inverse. The optical properties of latent fingermarks are quite different between drug addicts and non-drug users. This is a technic superiority for crime scene investigation to distinguish them. In this paper, we calculate the permittivity and permeability of drug metabolites using tight-binding model. The latent fingermarks of smokers and non-smokers are given as an example. PMID:26838730

Predictive Inference Using Latent Variables with Covariates*

PubMed Central

Schofield, Lynne Steuerle; Junker, Brian; Taylor, Lowell J.; Black, Dan A.

2014-01-01

Plausible Values (PVs) are a standard multiple imputation tool for analysis of large education survey data that measures latent proficiency variables. When latent proficiency is the dependent variable, we reconsider the standard institutionally-generated PV methodology and find it applies with greater generality than shown previously. When latent proficiency is an independent variable, we show that the standard institutional PV methodology produces biased inference because the institutional conditioning model places restrictions on the form of the secondary analysts’ model. We offer an alternative approach that avoids these biases based on the mixed effects structural equations (MESE) model of Schofield (2008). PMID:25231627

Vertical Profiles of Latent Heat Release over the Global Tropics using TRMM Rainfall Products from December 1997 to November 2002

NASA Technical Reports Server (NTRS)

Tao, W.-K.; Lang, S.; Simpson, J.; Meneghini, R.; Halverson, J.; Johnson, R.; Adler, R.

2003-01-01

NASA Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) derived rainfall information will be used to estimate the four-dimensional structure of global monthly latent heating and rainfall profiles over the global tropics from December 1997 to November 2000. Rainfall, latent heating and radar reflectivity structures between El Nino (DJF 1997-98) and La Nina (DJF 1998-99) will be examined and compared. The seasonal variation of heating over various geographic locations (i.e., oceanic vs continental, Indian ocean vs west Pacific, Africa vs. S. America ) will also be analyzed. In addition, the relationship between rainfall, latent heating (maximum heating level), radar reflectivity and SST is examined and will be presented in the meeting. The impact of random error and bias in stratiform percentage estimates from PR on latent heating profiles is studied and will also be presented in the meeting. The Goddard Cumulus Ensemble Model is being used to simulate various mesoscale convective systems that developed in different geographic locations. Specifically, the model estimated rainfall, radar reflectivity and latent heating profiles will be compared to observational data collected from TRMM field campaigns over the South China Sea in 1998 (SCSMEX), Brazil in 1999 (TRMM-LBA), and the central Pacific in 1999 (KWAJEX). Sounding diagnosed heating budgets and radar reflectivity from these experiments can provide the means to validate (heating product) as well as improve the GCE model. Review of other latent heating algorithms will be discussed in the workshop.

Bifactor latent structure of attention-deficit/hyperactivity disorder (ADHD)/oppositional defiant disorder (ODD) symptoms and first-order latent structure of sluggish cognitive tempo symptoms.

PubMed

Lee, SoYean; Burns, G Leonard; Beauchaine, Theodore P; Becker, Stephen P

2016-08-01

The objective was to determine if the latent structure of attention-deficit/hyperactivity disorder (ADHD) and oppositional defiant disorder (ODD) symptoms is best explained by a general disruptive behavior factor along with specific inattention (IN), hyperactivity/impulsivity (HI), and ODD factors (a bifactor model) whereas the latent structure of sluggish cognitive tempo (SCT) symptoms is best explained by a first-order factor independent of the bifactor model of ADHD/ODD. Parents' (n = 703) and teachers' (n = 366) ratings of SCT, ADHD-IN, ADHD-HI, and ODD symptoms on the Child and Adolescent Disruptive Behavior Inventory (CADBI) in a community sample of children (ages 5-13; 55% girls) were used to evaluate 4 models of symptom organization. Results indicated that a bifactor model of ADHD/ODD symptoms, in conjunction with a separate first-order SCT factor, was the best model for both parent and teacher ratings. The first-order SCT factor showed discriminant validity with the general disruptive behavior and specific IN factors in the bifactor model. In addition, higher scores on the SCT factor predicted greater academic and social impairment, even after controlling for the general disruptive behavior and 3 specific factors. Consistent with predictions from the trait-impulsivity etiological model of externalizing liability, a single, general disruptive behavior factor accounted for nearly all common variance in ADHD/ODD symptoms, whereas SCT symptoms represented a factor different from the general disruptive behavior and specific IN factor. These results provide additional support for distinguishing between SCT and ADHD-IN. The study also demonstrates how etiological models can be used to predict specific latent structures of symptom organization. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Comparison of Internet-based and paper-based questionnaires in Taiwan using multisample invariance approach.

PubMed

Yu, Sen-Chi; Yu, Min-Ning

2007-08-01

This study examines whether the Internet-based questionnaire is psychometrically equivalent to the paper-based questionnaire. A random sample of 2,400 teachers in Taiwan was divided into experimental and control groups. The experimental group was invited to complete the electronic form of the Chinese version of Center for Epidemiologic Studies Depression Scale (CES-D) placed on the Internet, whereas the control group was invited to complete the paper-based CES-D, which they received by mail. The multisample invariance approach, derived from structural equation modeling (SEM), was applied to analyze the collected data. The analytical results show that the two groups have equivalent factor structures in the CES-D. That is, the items in CES-D function equivalently in the two groups. Then the equality of latent mean test was performed. The latent means of "depressed mood," "positive affect," and "interpersonal problems" in CES-D are not significantly different between these two groups. However, the difference in the "somatic symptoms" latent means between these two groups is statistically significant at alpha = 0.01. But the Cohen's d statistics indicates that such differences in latent means do not apparently lead to a meaningful effect size in practice. Both CES-D questionnaires exhibit equal validity, reliability, and factor structures and exhibit a little difference in latent means. Therefore, the Internet-based questionnaire represents a promising alternative to the paper-based questionnaire.

Post-traumatic stress symptoms and structure among orphan and vulnerable children and adolescents in Zambia

PubMed Central

Familiar, Itziar; Murray, Laura; Gross, Alden; Skavenski, Stephanie; Jere, Elizabeth; Bass, Judith

2014-01-01

Background Scant information exists on PTSD symptoms and structure in youth from developing countries. Methods We describe the symptom profile and exposure to trauma experiences among 343 orphan and vulnerable children and adolescents from Zambia. We distinguished profiles of post-traumatic stress symptoms using latent class analysis. Results Average number of trauma-related symptoms (21.6; range 0-38) was similar across sex and age. Latent class model suggested 3 classes varying by level of severity: low (31% of the sample), medium (45% of the sample), and high (24% of the sample) symptomatology. Conclusions Results suggest that PTSD is a continuously distributed latent trait. PMID:25382359

A lattice protein with an amyloidogenic latent state: stability and folding kinetics.

PubMed

Palyanov, Andrey Yu; Krivov, Sergei V; Karplus, Martin; Chekmarev, Sergei F

2007-03-15

We have designed a model lattice protein that has two stable folded states, the lower free energy native state and a latent state of somewhat higher energy. The two states have a sizable part of their structures in common (two "alpha-helices") and differ in the content of "alpha-helices" and "beta-strands" in the rest of their structures; i.e. for the native state, this part is alpha-helical, and for the latent state it is composed of beta-strands. Thus, the lattice protein free energy surface mimics that of amyloidogenic proteins that form well organized fibrils under appropriate conditions. A Go-like potential was used and the folding process was simulated with a Monte Carlo method. To gain insight into the equilibrium free energy surface and the folding kinetics, we have combined standard approaches (reduced free energy surfaces, contact maps, time-dependent populations of the characteristic states, and folding time distributions) with a new approach. The latter is based on a principal coordinate analysis of the entire set of contacts, which makes possible the introduction of unbiased reaction coordinates and the construction of a kinetic network for the folding process. The system is found to have four characteristic basins, namely a semicompact globule, an on-pathway intermediate (the bifurcation basin), and the native and latent states. The bifurcation basin is shallow and consists of the structure common to the native and latent states, with the rest disorganized. On the basis of the simulation results, a simple kinetic model describing the transitions between the characteristic states was developed, and the rate constants for the essential transitions were estimated. During the folding process the system dwells in the bifurcation basin for a relatively short time before it proceeds to the native or latent state. We suggest that such a bifurcation may occur generally for proteins in which native and latent states have a sizable part of their structures in common. Moreover, there is the possibility of introducing changes in the system (e.g., mutations), which guide the system toward the native or misfolded state.

Latent Heating Retrievals Using the TRMM Precipitation Radar: A Multi-Seasonal Study

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Lang, S.; Meneghini, R.; Halverson, J.; Johnson, R.; Simpson, J.; Einaudi, Franco (Technical Monitor)

2001-01-01

Rainfall is a key link in the hydrologic cycle and is a primary heat source for the atmosphere. The vertical distribution of latent heat release, which is accompanied by rainfall, modulates the large-scale circulations of the tropics and in turn can impact midlatitude weather. This latent heat release is a consequence of phase changes between vapor, liquid, and solid water. Present largescale weather and climate models can simulate latent heat release only crudely, thus reducing their confidence in predictions on both global and regional scales. This paper represents the first attempt to use NASA Tropical Rainfall Measuring Mission (TRMM) rainfall information to estimate the four-dimensional structure of global monthly latent heating profiles over the global tropics from December 1997 to October 2000. The Goddard Convective-Stratiform. Heating (CSH) algorithm and TRMM precipitation radar data are used for this study. We will examine and compare the latent heating structures between 1997-1998 (winter) ENSO and 1998-2000 (non-ENSO). We will also examine over the tropics. The seasonal variation of heating over various geographic locations (i.e., oceanic vs continental; Indian oceans vs west Pacific; Africa vs S. America) will be also examined and compared. In addition, we will examine the relationship between latent heating (max heating level) and SST. The period of interest also coincides with several TRMM field campaigns that recently occurred over the South China Sea in 1998 (SCSMEX), Brazil in 1999 (TRMM-LBA), and in the central Pacific in 1999 (KWAJEX). Sounding diagnosed Q1 budgets from these experiments could provide a means of validating the retrieved profiles of latent heating from the CSH algorithm.

Measuring Latent Quantities

ERIC Educational Resources Information Center

McDonald, Roderick P.

2011-01-01

A distinction is proposed between measures and predictors of latent variables. The discussion addresses the consequences of the distinction for the true-score model, the linear factor model, Structural Equation Models, longitudinal and multilevel models, and item-response models. A distribution-free treatment of calibration and…

Discriminative latent models for recognizing contextual group activities.

PubMed

Lan, Tian; Wang, Yang; Yang, Weilong; Robinovitch, Stephen N; Mori, Greg

2012-08-01

In this paper, we go beyond recognizing the actions of individuals and focus on group activities. This is motivated from the observation that human actions are rarely performed in isolation; the contextual information of what other people in the scene are doing provides a useful cue for understanding high-level activities. We propose a novel framework for recognizing group activities which jointly captures the group activity, the individual person actions, and the interactions among them. Two types of contextual information, group-person interaction and person-person interaction, are explored in a latent variable framework. In particular, we propose three different approaches to model the person-person interaction. One approach is to explore the structures of person-person interaction. Differently from most of the previous latent structured models, which assume a predefined structure for the hidden layer, e.g., a tree structure, we treat the structure of the hidden layer as a latent variable and implicitly infer it during learning and inference. The second approach explores person-person interaction in the feature level. We introduce a new feature representation called the action context (AC) descriptor. The AC descriptor encodes information about not only the action of an individual person in the video, but also the behavior of other people nearby. The third approach combines the above two. Our experimental results demonstrate the benefit of using contextual information for disambiguating group activities.

Discriminative Latent Models for Recognizing Contextual Group Activities

PubMed Central

Lan, Tian; Wang, Yang; Yang, Weilong; Robinovitch, Stephen N.; Mori, Greg

2012-01-01

In this paper, we go beyond recognizing the actions of individuals and focus on group activities. This is motivated from the observation that human actions are rarely performed in isolation; the contextual information of what other people in the scene are doing provides a useful cue for understanding high-level activities. We propose a novel framework for recognizing group activities which jointly captures the group activity, the individual person actions, and the interactions among them. Two types of contextual information, group-person interaction and person-person interaction, are explored in a latent variable framework. In particular, we propose three different approaches to model the person-person interaction. One approach is to explore the structures of person-person interaction. Differently from most of the previous latent structured models, which assume a predefined structure for the hidden layer, e.g., a tree structure, we treat the structure of the hidden layer as a latent variable and implicitly infer it during learning and inference. The second approach explores person-person interaction in the feature level. We introduce a new feature representation called the action context (AC) descriptor. The AC descriptor encodes information about not only the action of an individual person in the video, but also the behavior of other people nearby. The third approach combines the above two. Our experimental results demonstrate the benefit of using contextual information for disambiguating group activities. PMID:22144516

The Peer Interaction in Primary School Questionnaire: Testing for Measurement Equivalence and Latent Mean Differences in Bullying between Gender in Egypt, Saudi Arabia and the USA

ERIC Educational Resources Information Center

Hussein, Mohamed Habashy

2010-01-01

The Peer Interaction in Primary School Questionnaire (PIPSQ) was developed to assess individuals' levels of bullying and victimization. This study used the approach of latent means analysis (LMA) within the framework of structural equation modeling (SEM) to explore the factor structure and gender differences associated with the PIPSQ in a sample…

A Latent Growth Curve Analysis of the Structure of Aggression, Drug Use, and Delinquent Behaviors and their Interrelations over Time in Urban and Rural Adolescents

ERIC Educational Resources Information Center

Farrell, Albert D.; Sullivan, Terri N.; Esposito, Layla E.; Meyer, Aleta L.; Valois, Robert F.

2005-01-01

Latent growth curve analysis was used to examine the structure and interrelations among aggression, drug use, and delinquent behavior during early adolescence. Five waves of data were collected from 667 students at three urban middle schools serving a predominantly African American population, and from a more ethnically diverse sample of 950…

The latent structure of alcohol misuse in young adults: Do taxometric results differ as a function of prior criminal history?

PubMed

Walters, Glenn D

2015-12-01

The purpose of this study was to determine whether the latent structure of alcohol misuse is categorical or continuous in male and female adults with and without a history of prior criminal offending. Data from 3452 (1530 male, 1922 female) 27-to-32 year old members of the National Longitudinal Study of Adolescent to Adult Health (Add Health) were subjected to taxometric analysis using three nonredundant taxometric procedures--mean above minus below a cut (MAMBAC), maximum covariance (MAXCOV), and latent mode factor analysis (L-Mode). Analyses produced results consistent with categorical latent structure in males with a previous history of criminal offending but not in males without a previous history of criminal offending or females with or without a history of criminal offending. The findings from the other groups were indeterminate for the most part (i.e., neither categorical nor continuous). The presumptive taxon was validated by testing differences in age of onset and frequency of criminal arrest and drunkenness between the putative taxon and the upper portion of the complement. As predicted, all four validation outcomes were significantly worse in the taxon group. On the basis of these results it is concluded that alcohol misuse in young adults may have features of both categorical and continuous latent structure and that the categorical aspects are more prominent in males with a history of offending behavior. Additional research is required to determine which aspects and features of alcohol misuse are categorical and which aspects and features are continuous. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Toward a Model-Based Approach to the Clinical Assessment of Personality Psychopathology

PubMed Central

Eaton, Nicholas R.; Krueger, Robert F.; Docherty, Anna R.; Sponheim, Scott R.

2015-01-01

Recent years have witnessed tremendous growth in the scope and sophistication of statistical methods available to explore the latent structure of psychopathology, involving continuous, discrete, and hybrid latent variables. The availability of such methods has fostered optimism that they can facilitate movement from classification primarily crafted through expert consensus to classification derived from empirically-based models of psychopathological variation. The explication of diagnostic constructs with empirically supported structures can then facilitate the development of assessment tools that appropriately characterize these constructs. Our goal in this paper is to illustrate how new statistical methods can inform conceptualization of personality psychopathology and therefore its assessment. We use magical thinking as example, because both theory and earlier empirical work suggested the possibility of discrete aspects to the latent structure of personality psychopathology, particularly forms of psychopathology involving distortions of reality testing, yet other data suggest that personality psychopathology is generally continuous in nature. We directly compared the fit of a variety of latent variable models to magical thinking data from a sample enriched with clinically significant variation in psychotic symptomatology for explanatory purposes. Findings generally suggested a continuous latent variable model best represented magical thinking, but results varied somewhat depending on different indices of model fit. We discuss the implications of the findings for classification and applied personality assessment. We also highlight some limitations of this type of approach that are illustrated by these data, including the importance of substantive interpretation, in addition to use of model fit indices, when evaluating competing structural models. PMID:24007309

Accurate calculation of mutational effects on the thermodynamics of inhibitor binding to p38α MAP kinase: a combined computational and experimental study.

PubMed

Zhu, Shun; Travis, Sue M; Elcock, Adrian H

2013-07-09

A major current challenge for drug design efforts focused on protein kinases is the development of drug resistance caused by spontaneous mutations in the kinase catalytic domain. The ubiquity of this problem means that it would be advantageous to develop fast, effective computational methods that could be used to determine the effects of potential resistance-causing mutations before they arise in a clinical setting. With this long-term goal in mind, we have conducted a combined experimental and computational study of the thermodynamic effects of active-site mutations on a well-characterized and high-affinity interaction between a protein kinase and a small-molecule inhibitor. Specifically, we developed a fluorescence-based assay to measure the binding free energy of the small-molecule inhibitor, SB203580, to the p38α MAP kinase and used it measure the inhibitor's affinity for five different kinase mutants involving two residues (Val38 and Ala51) that contact the inhibitor in the crystal structure of the inhibitor-kinase complex. We then conducted long, explicit-solvent thermodynamic integration (TI) simulations in an attempt to reproduce the experimental relative binding affinities of the inhibitor for the five mutants; in total, a combined simulation time of 18.5 μs was obtained. Two widely used force fields - OPLS-AA/L and Amber ff99SB-ILDN - were tested in the TI simulations. Both force fields produced excellent agreement with experiment for three of the five mutants; simulations performed with the OPLS-AA/L force field, however, produced qualitatively incorrect results for the constructs that contained an A51V mutation. Interestingly, the discrepancies with the OPLS-AA/L force field could be rectified by the imposition of position restraints on the atoms of the protein backbone and the inhibitor without destroying the agreement for other mutations; the ability to reproduce experiment depended, however, upon the strength of the restraints' force constant. Imposition of position restraints in corresponding simulations that used the Amber ff99SB-ILDN force field had little effect on their ability to match experiment. Overall, the study shows that both force fields can work well for predicting the effects of active-site mutations on small molecule binding affinities and demonstrates how a direct combination of experiment and computation can be a powerful strategy for developing an understanding of protein-inhibitor interactions.

Accuracy of free energies of hydration using CM1 and CM3 atomic charges.

PubMed

Udier-Blagović, Marina; Morales De Tirado, Patricia; Pearlman, Shoshannah A; Jorgensen, William L

2004-08-01

Absolute free energies of hydration (DeltaGhyd) have been computed for 25 diverse organic molecules using partial atomic charges derived from AM1 and PM3 wave functions via the CM1 and CM3 procedures of Cramer, Truhlar, and coworkers. Comparisons are made with results using charges fit to the electrostatic potential surface (EPS) from ab initio 6-31G* wave functions and from the OPLS-AA force field. OPLS Lennard-Jones parameters for the organic molecules were used together with the TIP4P water model in Monte Carlo simulations with free energy perturbation theory. Absolute free energies of hydration were computed for OPLS united-atom and all-atom methane by annihilating the solutes in water and in the gas phase, and absolute DeltaGhyd values for all other molecules were computed via transformation to one of these references. Optimal charge scaling factors were determined by minimizing the unsigned average error between experimental and calculated hydration free energies. The PM3-based charge models do not lead to lower average errors than obtained with the EPS charges for the subset of 13 molecules in the original study. However, improvement is obtained by scaling the CM1A partial charges by 1.14 and the CM3A charges by 1.15, which leads to average errors of 1.0 and 1.1 kcal/mol for the full set of 25 molecules. The scaled CM1A charges also yield the best results for the hydration of amides including the E/Z free-energy difference for N-methylacetamide in water. Copyright 2004 Wiley Periodicals, Inc.

Latent Structure Agreement Analysis

DTIC Science & Technology

1989-11-01

correct for bias in estimation of disease prevalence due to misclassification error [39]. Software Varying panel latent class agreement models can be...D., and L. M. Irwig, "Estimation of Test Error Rates, Disease Prevalence and Relative Risk from Misclassified Data: A Review," Journal of Clinical

Forensic applications of chemical imaging: latent fingerprint detection using visible absorption and luminescence.

PubMed

Exline, David L; Wallace, Christie; Roux, Claude; Lennard, Chris; Nelson, Matthew P; Treado, Patrick J

2003-09-01

Chemical imaging technology is a rapid examination technique that combines molecular spectroscopy and digital imaging, providing information on morphology, composition, structure, and concentration of a material. Among many other applications, chemical imaging offers an array of novel analytical testing methods, which limits sample preparation and provides high-quality imaging data essential in the detection of latent fingerprints. Luminescence chemical imaging and visible absorbance chemical imaging have been successfully applied to ninhydrin, DFO, cyanoacrylate, and luminescent dye-treated latent fingerprints, demonstrating the potential of this technology to aid forensic investigations. In addition, visible absorption chemical imaging has been applied successfully to visualize untreated latent fingerprints.

Pain and the defense response: structural equation modeling reveals a coordinated psychophysiological response to increasing painful stimulation.

PubMed

Donaldson, Gary W; Chapman, C Richard; Nakamura, Yoshi; Bradshaw, David H; Jacobson, Robert C; Chapman, Christopher N

2003-03-01

The defense response theory implies that individuals should respond to increasing levels of painful stimulation with correlated increases in affectively mediated psychophysiological responses. This paper employs structural equation modeling to infer the latent processes responsible for correlated growth in the pain report, evoked potential amplitudes, pupil dilation, and skin conductance of 92 normal volunteers who experienced 144 trials of three levels of increasingly painful electrical stimulation. The analysis assumed a two-level model of latent growth as a function of stimulus level. The first level of analysis formulated a nonlinear growth model for each response measure, and allowed intercorrelations among the parameters of these models across individuals. The second level of analysis posited latent process factors to account for these intercorrelations. The best-fitting parsimonious model suggests that two latent processes account for the correlations. One of these latent factors, the activation threshold, determines the initial threshold response, while the other, the response gradient, indicates the magnitude of the coherent increase in response with stimulus level. Collectively, these two second-order factors define the defense response, a broad construct comprising both subjective pain evaluation and physiological mechanisms.

Non-destructive forensic latent fingerprint acquisition with chromatic white light sensors

NASA Astrophysics Data System (ADS)

Leich, Marcus; Kiltz, Stefan; Dittmann, Jana; Vielhauer, Claus

2011-02-01

Non-destructive latent fingerprint acquisition is an emerging field of research, which, unlike traditional methods, makes latent fingerprints available for additional verification or further analysis like tests for substance abuse or age estimation. In this paper a series of tests is performed to investigate the overall suitability of a high resolution off-the-shelf chromatic white light sensor for the contact-less and non-destructive latent fingerprint acquisition. Our paper focuses on scanning previously determined regions with exemplary acquisition parameter settings. 3D height field and reflection data of five different latent fingerprints on six different types of surfaces (HDD platter, brushed metal, painted car body (metallic and non-metallic finish), blued metal, veneered plywood) are experimentally studied. Pre-processing is performed by removing low-frequency gradients. The quality of the results is assessed subjectively; no automated feature extraction is performed. Additionally, the degradation of the fingerprint during the acquisition period is observed. While the quality of the acquired data is highly dependent on surface structure, the sensor is capable of detecting the fingerprint on all sample surfaces. On blued metal the residual material is detected; however, the ridge line structure dissolves within minutes after fingerprint placement.

Construct validity evidence for the Male Role Norms Inventory-Short Form: A structural equation modeling approach using the bifactor model.

PubMed

Levant, Ronald F; Hall, Rosalie J; Weigold, Ingrid K; McCurdy, Eric R

2016-10-01

The construct validity of the Male Role Norms Inventory-Short Form (MRNI-SF) was assessed using a latent variable approach implemented with structural equation modeling (SEM). The MRNI-SF was specified as having a bifactor structure, and validation scales were also specified as latent variables. The latent variable approach had the advantages of separating effects of general and specific factors and controlling for some sources of measurement error. Data (N = 484) were from a diverse sample (38.8% men of color, 22.3% men of diverse sexualities) of community-dwelling and college men who responded to an online survey. The construct validity of the MRNI-SF General Traditional Masculinity Ideology factor was supported for all 4 of the proposed latent correlations with: (a) Male Role Attitudes Scale; (b) general factor of Conformity to Masculine Norms Inventory-46; (c) higher-order factor of Gender Role Conflict Scale; and (d) Personal Attributes Questionnaire-Masculinity Scale. Significant correlations with relevant other latent factors provided concurrent validity evidence for the MRNI-SF specific factors of Negativity toward Sexual Minorities, Importance of Sex, Restrictive Emotionality, and Toughness, with all 8 of the hypothesized relationships supported. However, 3 relationships concerning Dominance were not supported. (The construct validity of the remaining 2 MRNI-SF specific factors-Avoidance of Femininity and Self-Reliance through Mechanical Skills was not assessed.) Comparisons were made, and meaningful differences noted, between the latent correlations emphasized in this study and their raw variable counterparts. Results are discussed in terms of the advantages of an SEM approach and the unique characteristics of the bifactor model. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Opening mechanism of adenylate kinase can vary according to selected molecular dynamics force field

NASA Astrophysics Data System (ADS)

Unan, Hulya; Yildirim, Ahmet; Tekpinar, Mustafa

2015-07-01

Adenylate kinase is a widely used test case for many conformational transition studies. It performs a large conformational transition between closed and open conformations while performing its catalytic function. To understand conformational transition mechanism and impact of force field choice on E. Coli adenylate kinase, we performed all-atom explicit solvent classical molecular dynamics simulations starting from the closed conformation with four commonly used force fields, namely, Amber99, Charmm27, Gromos53a6, Opls-aa. We carried out 40 simulations, each one 200 ns. We analyzed completely 12 of them that show full conformational transition from the closed state to the open one. Our study shows that different force fields can have a bias toward different transition pathways. Transition time scales, frequency of conformational transitions, order of domain motions and free energy landscapes of each force field may also vary. In general, Amber99 and Charmm27 behave similarly while Gromos53a6 results have a resemblance to the Opls-aa force field results.

A Ricin Forensic Profiling Approach Based on a Complex Set of Biomarkers

DOE PAGES

Fredriksson, Sten-Ake; Wunschel, David S.; Lindstrom, Susanne Wiklund; ...

2018-03-28

A forensic method for the retrospective determination of preparation methods used for illicit ricin toxin production was developed. The method was based on a complex set of biomarkers, including carbohydrates, fatty acids, seed storage proteins, in combination with data on ricin and Ricinus communis agglutinin. The analyses were performed on samples prepared from four castor bean plant (R. communis) cultivars by four different sample preparation methods (PM1 – PM4) ranging from simple disintegration of the castor beans to multi-step preparation methods including different protein precipitation methods. Comprehensive analytical data was collected by use of a range of analytical methods andmore » robust orthogonal partial least squares-discriminant analysis- models (OPLS-DA) were constructed based on the calibration set. By the use of a decision tree and two OPLS-DA models, the sample preparation methods of test set samples were determined. The model statistics of the two models were good and a 100% rate of correct predictions of the test set was achieved.« less

A Ricin Forensic Profiling Approach Based on a Complex Set of Biomarkers

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

Fredriksson, Sten-Ake; Wunschel, David S.; Lindstrom, Susanne Wiklund

A forensic method for the retrospective determination of preparation methods used for illicit ricin toxin production was developed. The method was based on a complex set of biomarkers, including carbohydrates, fatty acids, seed storage proteins, in combination with data on ricin and Ricinus communis agglutinin. The analyses were performed on samples prepared from four castor bean plant (R. communis) cultivars by four different sample preparation methods (PM1 – PM4) ranging from simple disintegration of the castor beans to multi-step preparation methods including different protein precipitation methods. Comprehensive analytical data was collected by use of a range of analytical methods andmore » robust orthogonal partial least squares-discriminant analysis- models (OPLS-DA) were constructed based on the calibration set. By the use of a decision tree and two OPLS-DA models, the sample preparation methods of test set samples were determined. The model statistics of the two models were good and a 100% rate of correct predictions of the test set was achieved.« less

Molecular Dynamics Simulation Study of the Selectivity of a Silica Polymer for Ibuprofen

PubMed Central

Concu, Riccardo; Cordeiro, M. Natalia D. S.

2016-01-01

In the past few years, the sol-gel polycondensation technique has been increasingly employed with great success as an alternative approach to the preparation of molecularly imprinted materials (MIMs). The main aim of this study was to study, through a series of molecular dynamics (MD) simulations, the selectivity of an imprinted silica xerogel towards a new template—the (±)-2-(P-Isobutylphenyl) propionic acid (Ibuprofen, IBU). We have previously demonstrated the affinity of this silica xerogel toward a similar molecule. In the present study, we simulated the imprinting process occurring in a sol-gel mixture using the Optimized Potentials for Liquid Simulations-All Atom (OPLS-AA) force field, in order to evaluate the selectivity of this xerogel for a template molecule. In addition, for the first time, we have developed and verified a new parameterisation for the Ibuprofen® based on the OPLS-AA framework. To evaluate the selectivity of the polymer, we have employed both the radial distribution functions, interaction energies and cluster analyses. PMID:27399685

Molecular Dynamics Simulation Study of the Selectivity of a Silica Polymer for Ibuprofen.

PubMed

Concu, Riccardo; Cordeiro, M Natalia D S

2016-07-07

In the past few years, the sol-gel polycondensation technique has been increasingly employed with great success as an alternative approach to the preparation of molecularly imprinted materials (MIMs). The main aim of this study was to study, through a series of molecular dynamics (MD) simulations, the selectivity of an imprinted silica xerogel towards a new template-the (±)-2-(P-Isobutylphenyl) propionic acid (Ibuprofen, IBU). We have previously demonstrated the affinity of this silica xerogel toward a similar molecule. In the present study, we simulated the imprinting process occurring in a sol-gel mixture using the Optimized Potentials for Liquid Simulations-All Atom (OPLS-AA) force field, in order to evaluate the selectivity of this xerogel for a template molecule. In addition, for the first time, we have developed and verified a new parameterisation for the Ibuprofen(®) based on the OPLS-AA framework. To evaluate the selectivity of the polymer, we have employed both the radial distribution functions, interaction energies and cluster analyses.

A general class of multinomial mixture models for anuran calling survey data

USGS Publications Warehouse

Royle, J. Andrew; Link, W.A.

2005-01-01

We propose a general framework for modeling anuran abundance using data collected from commonly used calling surveys. The data generated from calling surveys are indices of calling intensity (vocalization of males) that do not have a precise link to actual population size and are sensitive to factors that influence anuran behavior. We formulate a model for calling-index data in terms of the maximum potential calling index that could be observed at a site (the 'latent abundance class'), given its underlying breeding population, and we focus attention on estimating the distribution of this latent abundance class. A critical consideration in estimating the latent structure is imperfect detection, which causes the observed abundance index to be less than or equal to the latent abundance class. We specify a multinomial sampling model for the observed abundance index that is conditional on the latent abundance class. Estimation of the latent abundance class distribution is based on the marginal likelihood of the index data, having integrated over the latent class distribution. We apply the proposed modeling framework to data collected as part of the North American Amphibian Monitoring Program (NAAMP).

A systematic literature review of PTSD's latent structure in the Diagnostic and Statistical Manual of Mental Disorders: DSM-IV to DSM-5.

PubMed

Armour, Cherie; Műllerová, Jana; Elhai, Jon D

2016-03-01

The factor structure of posttraumatic stress disorder (PTSD) has been widely researched, but consensus regarding the exact number and nature of factors is yet to be reached. The aim of the current study was to systematically review the extant literature on PTSD's latent structure in the Diagnostic and Statistical Manual of Mental Disorders (DSM) in order to identify the best-fitting model. One hundred and twelve research papers published after 1994 using confirmatory factor analysis and DSM-based measures of PTSD were included in the review. In the DSM-IV literature, four-factor models received substantial support, but the five-factor Dysphoric arousal model demonstrated the best fit, regardless of gender, measurement instrument or trauma type. The recently proposed DSM-5 PTSD model was found to be a good representation of PTSD's latent structure, but studies analysing the six- and seven-factor models suggest that the DSM-5 PTSD factor structure may need further alterations. Copyright © 2015 Elsevier Ltd. All rights reserved.

Modeling Bivariate Change in Individual Differences: Prospective Associations Between Personality and Life Satisfaction.

PubMed

Hounkpatin, Hilda Osafo; Boyce, Christopher J; Dunn, Graham; Wood, Alex M

2017-09-18

A number of structural equation models have been developed to examine change in 1 variable or the longitudinal association between 2 variables. The most common of these are the latent growth model, the autoregressive cross-lagged model, the autoregressive latent trajectory model, and the latent change score model. The authors first overview each of these models through evaluating their different assumptions surrounding the nature of change and how these assumptions may result in different data interpretations. They then, to elucidate these issues in an empirical example, examine the longitudinal association between personality traits and life satisfaction. In a representative Dutch sample (N = 8,320), with participants providing data on both personality and life satisfaction measures every 2 years over an 8-year period, the authors reproduce findings from previous research. However, some of the structural equation models overviewed have not previously been applied to the personality-life satisfaction relation. The extended empirical examination suggests intraindividual changes in life satisfaction predict subsequent intraindividual changes in personality traits. The availability of data sets with 3 or more assessment waves allows the application of more advanced structural equation models such as the autoregressive latent trajectory or the extended latent change score model, which accounts for the complex dynamic nature of change processes and allows stronger inferences on the nature of the association between variables. However, the choice of model should be determined by theories of change processes in the variables being studied. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Measurement Model Specification Error in LISREL Structural Equation Models.

ERIC Educational Resources Information Center

Baldwin, Beatrice; Lomax, Richard

This LISREL study examines the robustness of the maximum likelihood estimates under varying degrees of measurement model misspecification. A true model containing five latent variables (two endogenous and three exogenous) and two indicator variables per latent variable was used. Measurement model misspecification considered included errors of…

Implicit measurement of the latent heat in a magnetocaloric NiMnIn Heusler alloy

NASA Astrophysics Data System (ADS)

Ghahremani, Mohammadreza; ElBidweihy, Hatem; Bennett, Lawrence H.; Della Torre, Edward; Zou, Min; Johnson, Francis

2013-05-01

The latent heat linked with the first-order transformation of a NiMnIn Heusler alloy has been studied through direct measurements of the adiabatic temperature change, ΔTad, during magnetization process. The experimental procedure used guarantees independent data points and negates any contribution of hysteretic losses to the magnetocaloric effect. Thus, the differences between the magnitudes of ΔTad measurements during the magnetization with the initial temperature change directions from low-to-high and high-to-low are solely attributed to the latent heat exchange, which accompanies the irreversible structural first-order transformation. An estimate of the latent heat inducing such differences is about 0.292 J/g.

Effect of carbon spacer length on zwitterionic carboxybetaines.

PubMed

Shao, Qing; Jiang, Shaoyi

2013-02-07

Zwitterionic carboxybetaines (CBs) are ubiquitous in nature and considered promising materials for biological and chemical applications. A thorough understanding of the effect of carbon spacer length (CSL) on molecular properties is important. In this work, using molecular dynamics simulation and quantum chemical calculation, we investigated the effect of CSL on the molecular properties of CB molecules. The hydration number, structure, and dynamics of carboxylic and trimethyl ammonium groups were investigated and found to present different behaviors in regards to the variation of CSL. The simulation results with partial charges developed from quantum chemical calculations were compared with those with partial charges from the OPLS all atom (OPLSAA) force field. The hydration free energy of CB molecules and CB-Na(+) association was also studied as a function of CSL.

Behavioral Scale Reliability and Measurement Invariance Evaluation Using Latent Variable Modeling

ERIC Educational Resources Information Center

Raykov, Tenko

2004-01-01

A latent variable modeling approach to reliability and measurement invariance evaluation for multiple-component measuring instruments is outlined. An initial discussion deals with the limitations of coefficient alpha, a frequently used index of composite reliability. A widely and readily applicable structural modeling framework is next described…

Working Memory Tasks Differ in Factor Structure across Age Cohorts: Implications for Dedifferentiation

ERIC Educational Resources Information Center

Johnson, Wendy; Logie, Robert H.; Brockmole, James R.

2010-01-01

Researchers interested in working memory have debated whether it should be considered a single latent cognitive ability or a set of essentially independent latent abilities distinguished by domain-specific memory and/or processing resources. Simultaneously, researchers interested in cognitive aging have established that there are substantial…

Evaluation of Validity and Reliability for Hierarchical Scales Using Latent Variable Modeling

ERIC Educational Resources Information Center

Raykov, Tenko; Marcoulides, George A.

2012-01-01

A latent variable modeling method is outlined, which accomplishes estimation of criterion validity and reliability for a multicomponent measuring instrument with hierarchical structure. The approach provides point and interval estimates for the scale criterion validity and reliability coefficients, and can also be used for testing composite or…

Diagnostic Procedures for Detecting Nonlinear Relationships between Latent Variables

ERIC Educational Resources Information Center

Bauer, Daniel J.; Baldasaro, Ruth E.; Gottfredson, Nisha C.

2012-01-01

Structural equation models are commonly used to estimate relationships between latent variables. Almost universally, the fitted models specify that these relationships are linear in form. This assumption is rarely checked empirically, largely for lack of appropriate diagnostic techniques. This article presents and evaluates two procedures that can…

Latent Heating from TRMM Satellite Measurements

NASA Technical Reports Server (NTRS)

Tao, W.-K.; Smith, E.; Olson, W.

2005-01-01

Rainfall production is a fundamental process within the Earth;s hydrological cycle because it represents both a principal forcing term in surface water budgets, and its energetics corollary, latent heating, is the principal source of atmospheric diabatic heating. Latent heat release itself is a consequence of phase changes between the vapor, liquid, and frozen states of water. The properties of the vertical distribution of latent heat release modulate large-scale meridional and zonal circulations with the Tropics - as well as modify the energetic efficiencies of mid-latitude weather systems. This paper highlights the retrieval of observatory, which was launched in November 1997 as a joint American-Japanese space endeavor. Since then, TRMM measurements have been providing an accurate four-dimensional amount of rainfall over the global Tropics and sub-tropics - information which can be used to estimate the spacetime structure of latent heating across the Earth's low latitudes. A set of algorithm methodologies has and continues to be developed to estimate latent heating based on rain rate profile retrievals obtained from TRMM measurements. These algorithms are briefly described followed by a discussion of the foremost latent heating products that can be generate from them. The investigation then provides an overview of how TRMM-derived latent heating information is currently being used in conjunction with global weather and climate models, concluding with remarks intended to stimulate further research on latent heating retrieval from satellites.

Vertical Profiles of Latent Heat Release over the Global Tropics using TRMM rainfall products from December 1997 to November 2001

NASA Technical Reports Server (NTRS)

Tao, W.-K.; Lang, S.; Simpson, J.; Meneghini, R.; Halverson, J.; Johnson, R.; Adler, R.

2002-01-01

NASA Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) derived rainfall information will be used to estimate the four-dimensional structure of global monthly latent heating and rainfall profiles over the global tropics from December 1997 to November 2001. Rainfall, latent heating and radar reflectivity structures between El Nino (DE 1997-98) and La Nina (DJF 1998-99) will be examined and compared. The seasonal variation of heating over various geographic locations (i.e., oceanic vs continental, Indian ocean vs. west Pacific, Africa vs. S. America) will also be analyzed. In addition, the relationship between rainfall, latent heating (maximum heating level), radar reflectivity and SST is examined and will be presented in the meeting. The impact of random error and bias in strtaiform percentage estimates from PR on latent heating profiles is studied and will also be presented in the meeting. The Goddard Cumulus Ensemble Model is being used to simulate various mesoscale convective systems that developed in different geographic locations. Specifically, the model estimated rainfall, radar reflectivity and latent heating profiles will be compared to observational data collected from TRMM field campaigns over the South China Sea in 1998 (SCSMEX), Brazil in 1999 (TRMM-LBA), and the central Pacific in 1999 (KWAJEX). Sounding diagnosed heating budgets and radar reflectivity from these experiments can provide the means to validate (heating product) as well as improve the GCE model.

Vertical Profiles of Latent Heat Release Over the Global Tropics using TRMM Rainfall Products from December 1997 to November 2001

NASA Technical Reports Server (NTRS)

Tao, W.-K.; Lang, S.; Simpson, J.; Meneghini, R.; Halverson, J.; Johnson, R.; Adler, R.; Starr, David (Technical Monitor)

2002-01-01

NASA Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) derived rainfall information will be used to estimate the four-dimensional structure of global monthly latent heating and rainfall profiles over the global tropics from December 1997 to November 2000. Rainfall, latent heating and radar reflectivity structures between El Nino (DJF 1997-98) and La Nina (DJF 1998-99) will be examined and compared. The seasonal variation of heating over various geographic locations (i.e., oceanic vs continental, Indian ocean vs west Pacific, Africa vs S. America) will also be analyzed. In addition, the relationship between rainfall, latent heating (maximum heating level), radar reflectivity and SST is examined and will be presented in the meeting. The impact of random error and bias in stratiform percentage estimates from PR on latent heating profiles is studied and will also be presented in the meeting. The Goddard Cumulus Ensemble Model is being used to simulate various mesoscale convective systems that developed in different geographic locations. Specifically, the model estimated rainfall, radar reflectivity and latent heating profiles will be compared to observational data collected from TRMM field campaigns over the South China Sea in 1998 (SCSMEX), Brazil in 1999 (TRMM-LBA), and the central Pacific in 1999 (KWAJEX). Sounding diagnosed heating budgets and radar reflectivity from these experiments can provide the means to validate (heating product) as well as improve the GCE model.

Vertical Profiles of Latent Heat Release over the Global Tropics Using TRMM Rainfall Products from December 1997 to November 2002

NASA Technical Reports Server (NTRS)

Tao, W.-K.

2003-01-01

NASA Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) derived rainfall information will be used to estimate the four-dimensional structure of global monthly latent heating and rainfall profiles over the global tropics from December 1997 to November 2000. Rainfall, latent heating and radar reflectivity structures between El Nino (DJF 1997-98) and La Nina (DJF 1998-99) will be examined and compared. The seasonal variation of heating over various geographic locations (i.e., oceanic vs continental, Indian ocean vs west Pacific, Africa vs S. America) will also be analyzed. In addition, the relationship between rainfall, latent heating (maximum heating level), radar reflectivity and SST is examined and will be presented in the meeting. The impact of random error and bias in straitform percentage estimates from PR on latent heating profiles is studied and will also be presented in the meeting. The Goddard Cumulus Ensemble Model is being used to simulate various mesoscale convective systems that developed in different geographic locations. Specifically, the model estimated rainfall, radar reflectivity and latent heating profiles will be compared to observational data collected from TRMM field campaigns over the South China Sea in 1998 (SCSMXX), Brazil in 1999 (TRMM- LBA), and the central Pacific in 1999 (KWAJEX). Sounding diagnosed heating budgets and radar reflectivity from these experiments can provide the means to validate (heating product) as well as improve the GCE model.

Heterogeneity of sleep quality in relation to circadian preferences and depressive symptomatology among major depressive patients.

PubMed

Selvi, Yavuz; Boysan, Murat; Kandeger, Ali; Uygur, Omer F; Sayin, Ayca A; Akbaba, Nursel; Koc, Basak

2018-08-01

The current study aimed at investigating the latent dimensional structure of sleep quality as indexed by the seven components of the Pittsburgh Sleep Quality Index (PSQI), as well as latent covariance structure between sleep quality, circadian preferences and depressive symptoms. Two hundred twenty-five patients with major depressive disorder (MDD), with an average age of 29.92 ± 10.49 years (aged between 17 and 63), participated in the study. The PSQI, Morningness-Eveningness Questionnaire (MEQ) and Beck Depression Inventory (BDI) were administered to participants. Four sets of latent class analyses were subsequently run to obtain optimal number of latent classes best fit to the data. Mixture models revealed that sleep quality is multifaceted in MDD. The data best fit to four-latent-class model: Poor Habitual Sleep Quality (PHSQ), Poor Subjective Sleep Quality (PSSQ), Intermediate Sleep Quality (ISQ), and Good Sleep Quality (GSQ). MDD patients classified into GSQ latent class (23.6%) reported the lowest depressive symptoms and were more prone to morningness diurnal preferences compared to other three homogenous sub-groups. Finally, the significant association between eveningness diurnal preferences and depressive symptomatology was significantly mediated by poor sleep quality. The cross-sectional nature of the study and the lack of an objective measurement of sleep such as polysomnography recordings was the most striking limitation of the study. We concluded sleep quality in relation to circadian preferences and depressive symptoms has a heterogeneous nature in MDD. Copyright © 2018. Published by Elsevier B.V.

Latent geometry of bipartite networks

NASA Astrophysics Data System (ADS)

Kitsak, Maksim; Papadopoulos, Fragkiskos; Krioukov, Dmitri

2017-03-01

Despite the abundance of bipartite networked systems, their organizing principles are less studied compared to unipartite networks. Bipartite networks are often analyzed after projecting them onto one of the two sets of nodes. As a result of the projection, nodes of the same set are linked together if they have at least one neighbor in common in the bipartite network. Even though these projections allow one to study bipartite networks using tools developed for unipartite networks, one-mode projections lead to significant loss of information and artificial inflation of the projected network with fully connected subgraphs. Here we pursue a different approach for analyzing bipartite systems that is based on the observation that such systems have a latent metric structure: network nodes are points in a latent metric space, while connections are more likely to form between nodes separated by shorter distances. This approach has been developed for unipartite networks, and relatively little is known about its applicability to bipartite systems. Here, we fully analyze a simple latent-geometric model of bipartite networks and show that this model explains the peculiar structural properties of many real bipartite systems, including the distributions of common neighbors and bipartite clustering. We also analyze the geometric information loss in one-mode projections in this model and propose an efficient method to infer the latent pairwise distances between nodes. Uncovering the latent geometry underlying real bipartite networks can find applications in diverse domains, ranging from constructing efficient recommender systems to understanding cell metabolism.

Identification of a discriminative metabolomic fingerprint of potential clinical relevance in saliva of patients with periodontitis using 1H nuclear magnetic resonance (NMR) spectroscopy.

PubMed

Rzeznik, Matthias; Triba, Mohamed Nawfal; Levy, Pierre; Jungo, Sébastien; Botosoa, Eliot; Duchemann, Boris; Le Moyec, Laurence; Bernaudin, Jean-François; Savarin, Philippe; Guez, Dominique

2017-01-01

Periodontitis is characterized by the loss of the supporting tissues of the teeth in an inflammatory-infectious context. The diagnosis relies on clinical and X-ray examination. Unfortunately, clinical signs of tissue destruction occur late in the disease progression. Therefore, it is mandatory to identify reliable biomarkers to facilitate a better and earlier management of this disease. To this end, saliva represents a promising fluid for identification of biomarkers as metabolomic fingerprints. The present study used high-resolution 1H-nuclear magnetic resonance (NMR) spectroscopy coupled with multivariate statistical analysis to identify the metabolic signature of active periodontitis. The metabolome of stimulated saliva of 26 patients with generalized periodontitis (18 chronic and 8 aggressive) was compared to that of 25 healthy controls. Principal Components Analysis (PCA), performed with clinical variables, indicated that the patient population was homogeneous, demonstrating a strong correlation between the clinical and the radiological variables used to assess the loss of periodontal tissues and criteria of active disease. Orthogonal Projection to Latent Structure (OPLS) analysis showed that patients with periodontitis can be discriminated from controls on the basis of metabolite concentrations in saliva with satisfactory explained variance (R2X = 0.81 and R2Y = 0.61) and predictability (Q2Y = 0.49, CV-AUROC = 0.94). Interestingly, this discrimination was irrespective of the type of generalized periodontitis, i.e. chronic or aggressive. Among the main discriminating metabolites were short chain fatty acids as butyrate, observed in higher concentrations, and lactate, γ-amino-butyrate, methanol, and threonine observed in lower concentrations in periodontitis. The association of lactate, GABA, and butyrate to generate an aggregated variable reached the best positive predictive value for diagnosis of periodontitis. In conclusion, this pilot study showed that 1H-NMR spectroscopy analysis of saliva could differentiate patients with periodontitis from controls. Therefore, this simple, robust, non-invasive method, may offer a significant help for early diagnosis and follow-up of periodontitis.

Application of a MRI based index to longitudinal atrophy change in Alzheimer disease, mild cognitive impairment and healthy older individuals in the AddNeuroMed cohort

PubMed Central

Aguilar, Carlos; Muehlboeck, J-Sebastian; Mecocci, Patrizia; Vellas, Bruno; Tsolaki, Magda; Kloszewska, Iwona; Soininen, Hilkka; Lovestone, Simon; Wahlund, Lars-Olof; Simmons, Andrew; Westman, Eric

2014-01-01

Cross sectional studies of patients at risk of developing Alzheimer disease (AD) have identified several brain regions known to be prone to degeneration suitable as biomarkers, including hippocampal, ventricular, and whole brain volume. The aim of this study was to longitudinally evaluate an index based on morphometric measures derived from MRI data that could be used for classification of AD and healthy control subjects, as well as prediction of conversion from mild cognitive impairment (MCI) to AD. Patients originated from the AddNeuroMed project at baseline (119 AD, 119 MCI, 110 controls (CTL)) and 1-year follow-up (62 AD, 73 MCI, 79 CTL). Data consisted of 3D T1-weighted MR images, demographics, MMSE, ADAS-Cog, CERAD and CDR scores, and APOE e4 status. We computed an index using a multivariate classification model (AD vs. CTL), using orthogonal partial least squares to latent structures (OPLS). Sensitivity, specificity and AUC were determined. Performance of the classifier (AD vs. CTL) was high at baseline (10-fold cross-validation, 84% sensitivity, 91% specificity, 0.93 AUC) and at 1-year follow-up (92% sensitivity, 74% specificity, 0.93 AUC). Predictions of conversion from MCI to AD were good at baseline (77% of MCI converters) and at follow-up (91% of MCI converters). MCI carriers of the APOE e4 allele manifested more atrophy and presented a faster cognitive decline when compared to non-carriers. The derived index demonstrated a steady increase in atrophy over time, yielding higher accuracy in prediction at the time of clinical conversion. Neuropsychological tests appeared less sensitive to changes over time. However, taking the average of the two time points yielded better correlation between the index and cognitive scores as opposed to using cross-sectional data only. Thus, multivariate classification seemed to detect patterns of AD changes before conversion from MCI to AD and including longitudinal information is of great importance. PMID:25071554

Identification of a discriminative metabolomic fingerprint of potential clinical relevance in saliva of patients with periodontitis using 1H nuclear magnetic resonance (NMR) spectroscopy

PubMed Central

Levy, Pierre; Jungo, Sébastien; Botosoa, Eliot; Duchemann, Boris; Le Moyec, Laurence; Bernaudin, Jean-François; Guez, Dominique

2017-01-01

Periodontitis is characterized by the loss of the supporting tissues of the teeth in an inflammatory-infectious context. The diagnosis relies on clinical and X-ray examination. Unfortunately, clinical signs of tissue destruction occur late in the disease progression. Therefore, it is mandatory to identify reliable biomarkers to facilitate a better and earlier management of this disease. To this end, saliva represents a promising fluid for identification of biomarkers as metabolomic fingerprints. The present study used high-resolution 1H-nuclear magnetic resonance (NMR) spectroscopy coupled with multivariate statistical analysis to identify the metabolic signature of active periodontitis. The metabolome of stimulated saliva of 26 patients with generalized periodontitis (18 chronic and 8 aggressive) was compared to that of 25 healthy controls. Principal Components Analysis (PCA), performed with clinical variables, indicated that the patient population was homogeneous, demonstrating a strong correlation between the clinical and the radiological variables used to assess the loss of periodontal tissues and criteria of active disease. Orthogonal Projection to Latent Structure (OPLS) analysis showed that patients with periodontitis can be discriminated from controls on the basis of metabolite concentrations in saliva with satisfactory explained variance (R2X = 0.81 and R2Y = 0.61) and predictability (Q2Y = 0.49, CV-AUROC = 0.94). Interestingly, this discrimination was irrespective of the type of generalized periodontitis, i.e. chronic or aggressive. Among the main discriminating metabolites were short chain fatty acids as butyrate, observed in higher concentrations, and lactate, γ-amino-butyrate, methanol, and threonine observed in lower concentrations in periodontitis. The association of lactate, GABA, and butyrate to generate an aggregated variable reached the best positive predictive value for diagnosis of periodontitis. In conclusion, this pilot study showed that 1H-NMR spectroscopy analysis of saliva could differentiate patients with periodontitis from controls. Therefore, this simple, robust, non-invasive method, may offer a significant help for early diagnosis and follow-up of periodontitis. PMID:28837579

Application of Ultra-performance Liquid Chromatography with Time-of-Flight Mass Spectrometry for the Rapid Analysis of Constituents and Metabolites from the Extracts of Acanthopanax senticosus Harms Leaf

PubMed Central

Zhang, Yingzhi; Zhang, Aihua; Zhang, Ying; Sun, Hui; Meng, Xiangcai; Yan, Guangli; Wang, Xijun

2016-01-01

Acanthopanax senticosus (Rupr and Maxim) Harms (AS), a member of Araliaceae family, is a typical folk medicinal herb, which is widely distributed in the Northeastern part of China. Due to lack of this resource caused by the extensive use of its root, this work studied the chemical constituents of leaves of this plant with the purpose of looking for an alternative resource. In this work, a fast and optimized ultra-performance liquid chromatography method with quadrupole time-of-flight mass spectrometry (UPLC-QTOF-MS) has been developed for the analysis of constituents in leaves extracts. A total of 131 compounds were identified or tentatively characterized including triterpenoid saponins, phenols, flavonoids, lignans, coumarins, polysaccharides, and other compounds based on their fragmentation behaviors. Besides, a total of 21 metabolites were identified in serum in rats after oral administration, among which 12 prototypes and 9 metabolites through the metabolic pathways of reduction, methylation, sulfate conjugation, sulfoxide to thioether and deglycosylation. The coupling of UPLC-QTOF-MS led to the in-depth characterization of the leaves extracts of AS both in vitro and in vivo on the basis of retention time, mass accuracy, and tandem MS/MS spectra. It concluded that this analytical tool was very valuable in the study of complex compounds in medicinal herb. HIGHLIGHT OF PAPER A fast UPLC-QTOF-MS has been developed for analysis of constituents in leaves extractsA total of 131 compounds were identified in leaves extractsA total of 21 metabolites including 12 prototypes and 9 metabolites were identified in vivo. SUMMARY Constituent’s analysis of Acanthopanax senticosus Harms leaf by ultra-performance liquid chromatography method with quadrupole time-of-flight mass spectrometry. Abbreviations used: AS: Acanthopanax senticosus (Rupr and Maxim) Harms, TCHM: Traditional Chinese herbal medicine, UPLC-QTOF-MS: Ultra-performance liquid chromatography method with time-of-flight mass spectrometry, MS/MS: Tandem mass spectrometry, PCA: Principal component analysis, PLS-DA: Partial least squared discriminant analysis, OPLS-DA: Orthogonal projection to latent structure-discriminant analysis. PMID:27076752

Multivariate estimation of the limit of detection by orthogonal partial least squares in temperature-modulated MOX sensors.

PubMed

Burgués, Javier; Marco, Santiago

2018-08-17

Metal oxide semiconductor (MOX) sensors are usually temperature-modulated and calibrated with multivariate models such as partial least squares (PLS) to increase the inherent low selectivity of this technology. The multivariate sensor response patterns exhibit heteroscedastic and correlated noise, which suggests that maximum likelihood methods should outperform PLS. One contribution of this paper is the comparison between PLS and maximum likelihood principal components regression (MLPCR) in MOX sensors. PLS is often criticized by the lack of interpretability when the model complexity increases beyond the chemical rank of the problem. This happens in MOX sensors due to cross-sensitivities to interferences, such as temperature or humidity and non-linearity. Additionally, the estimation of fundamental figures of merit, such as the limit of detection (LOD), is still not standardized in multivariate models. Orthogonalization methods, such as orthogonal projection to latent structures (O-PLS), have been successfully applied in other fields to reduce the complexity of PLS models. In this work, we propose a LOD estimation method based on applying the well-accepted univariate LOD formulas to the scores of the first component of an orthogonal PLS model. The resulting LOD is compared to the multivariate LOD range derived from error-propagation. The methodology is applied to data extracted from temperature-modulated MOX sensors (FIS SB-500-12 and Figaro TGS 3870-A04), aiming at the detection of low concentrations of carbon monoxide in the presence of uncontrolled humidity (chemical noise). We found that PLS models were simpler and more accurate than MLPCR models. Average LOD values of 0.79 ppm (FIS) and 1.06 ppm (Figaro) were found using the approach described in this paper. These values were contained within the LOD ranges obtained with the error-propagation approach. The mean LOD increased to 1.13 ppm (FIS) and 1.59 ppm (Figaro) when considering validation samples collected two weeks after calibration, which represents a 43% and 46% degradation, respectively. The orthogonal score-plot was a very convenient tool to visualize MOX sensor data and to validate the LOD estimates. Copyright © 2018 Elsevier B.V. All rights reserved.

Exploring context and content links in social media: a latent space method.

PubMed

Qi, Guo-Jun; Aggarwal, Charu; Tian, Qi; Ji, Heng; Huang, Thomas S

2012-05-01

Social media networks contain both content and context-specific information. Most existing methods work with either of the two for the purpose of multimedia mining and retrieval. In reality, both content and context information are rich sources of information for mining, and the full power of mining and processing algorithms can be realized only with the use of a combination of the two. This paper proposes a new algorithm which mines both context and content links in social media networks to discover the underlying latent semantic space. This mapping of the multimedia objects into latent feature vectors enables the use of any off-the-shelf multimedia retrieval algorithms. Compared to the state-of-the-art latent methods in multimedia analysis, this algorithm effectively solves the problem of sparse context links by mining the geometric structure underlying the content links between multimedia objects. Specifically for multimedia annotation, we show that an effective algorithm can be developed to directly construct annotation models by simultaneously leveraging both context and content information based on latent structure between correlated semantic concepts. We conduct experiments on the Flickr data set, which contains user tags linked with images. We illustrate the advantages of our approach over the state-of-the-art multimedia retrieval techniques.

Retrieved Vertical Profiles of Latent Heat Release Using TRMM Rainfall Products

NASA Technical Reports Server (NTRS)

Tao, W.-K.; Lang, S.; Olson, W. S.; Meneghini, R.; Yang, S.; Simpson, J.; Kummerow, C.; Smith, E.

2000-01-01

This paper represents the first attempt to use TRMM rainfall information to estimate the four dimensional latent heating structure over the global tropics for February 1998. The mean latent heating profiles over six oceanic regions (TOGA COARE IFA, Central Pacific, S. Pacific Convergence Zone, East Pacific, Indian Ocean and Atlantic Ocean) and three continental regions (S. America, Central Africa and Australia) are estimated and studied. The heating profiles obtained from the results of diagnostic budget studies over a broad range of geographic locations are used to provide comparisons and indirect validation for the heating algorithm estimated heating profiles. Three different latent heating algorithms, the Goddard Convective-Stratiform (CSH) heating, the Goddard Profiling (GPROF) heating, and the Hydrometeor heating (HH) are used and their results are intercompared. The horizontal distribution or patterns of latent heat release from the three different heating retrieval methods are quite similar. They all can identify the areas of major convective activity (i.e., a well defined ITCZ in the Pacific, a distinct SPCZ) in the global tropics. The magnitude of their estimated latent heating release is also not in bad agreement with each other and with those determined from diagnostic budget studies. However, the major difference among these three heating retrieval algorithms is the altitude of the maximum heating level. The CSH algorithm estimated heating profiles only show one maximum heating level, and the level varies between convective activity from various geographic locations. These features are in good agreement with diagnostic budget studies. By contrast, two maximum heating levels were found using the GPROF heating and HH algorithms. The latent heating profiles estimated from all three methods can not show cooling between active convective events. We also examined the impact of different TMI (Multi-channel Passive Microwave Sensor) and PR (Precipitation Radar) rainfall information on latent heating structures.

The Importance of Isomorphism for Conclusions about Homology: A Bayesian Multilevel Structural Equation Modeling Approach with Ordinal Indicators.

PubMed

Guenole, Nigel

2016-01-01

We describe a Monte Carlo study examining the impact of assuming item isomorphism (i.e., equivalent construct meaning across levels of analysis) on conclusions about homology (i.e., equivalent structural relations across levels of analysis) under varying degrees of non-isomorphism in the context of ordinal indicator multilevel structural equation models (MSEMs). We focus on the condition where one or more loadings are higher on the between level than on the within level to show that while much past research on homology has ignored the issue of psychometric isomorphism, psychometric isomorphism is in fact critical to valid conclusions about homology. More specifically, when a measurement model with non-isomorphic items occupies an exogenous position in a multilevel structural model and the non-isomorphism of these items is not modeled, the within level exogenous latent variance is under-estimated leading to over-estimation of the within level structural coefficient, while the between level exogenous latent variance is overestimated leading to underestimation of the between structural coefficient. When a measurement model with non-isomorphic items occupies an endogenous position in a multilevel structural model and the non-isomorphism of these items is not modeled, the endogenous within level latent variance is under-estimated leading to under-estimation of the within level structural coefficient while the endogenous between level latent variance is over-estimated leading to over-estimation of the between level structural coefficient. The innovative aspect of this article is demonstrating that even minor violations of psychometric isomorphism render claims of homology untenable. We also show that posterior predictive p-values for ordinal indicator Bayesian MSEMs are insensitive to violations of isomorphism even when they lead to severely biased within and between level structural parameters. We highlight conditions where poor estimation of even correctly specified models rules out empirical examination of isomorphism and homology without taking precautions, for instance, larger Level-2 sample sizes, or using informative priors.

The Importance of Isomorphism for Conclusions about Homology: A Bayesian Multilevel Structural Equation Modeling Approach with Ordinal Indicators

PubMed Central

Guenole, Nigel

2016-01-01

We describe a Monte Carlo study examining the impact of assuming item isomorphism (i.e., equivalent construct meaning across levels of analysis) on conclusions about homology (i.e., equivalent structural relations across levels of analysis) under varying degrees of non-isomorphism in the context of ordinal indicator multilevel structural equation models (MSEMs). We focus on the condition where one or more loadings are higher on the between level than on the within level to show that while much past research on homology has ignored the issue of psychometric isomorphism, psychometric isomorphism is in fact critical to valid conclusions about homology. More specifically, when a measurement model with non-isomorphic items occupies an exogenous position in a multilevel structural model and the non-isomorphism of these items is not modeled, the within level exogenous latent variance is under-estimated leading to over-estimation of the within level structural coefficient, while the between level exogenous latent variance is overestimated leading to underestimation of the between structural coefficient. When a measurement model with non-isomorphic items occupies an endogenous position in a multilevel structural model and the non-isomorphism of these items is not modeled, the endogenous within level latent variance is under-estimated leading to under-estimation of the within level structural coefficient while the endogenous between level latent variance is over-estimated leading to over-estimation of the between level structural coefficient. The innovative aspect of this article is demonstrating that even minor violations of psychometric isomorphism render claims of homology untenable. We also show that posterior predictive p-values for ordinal indicator Bayesian MSEMs are insensitive to violations of isomorphism even when they lead to severely biased within and between level structural parameters. We highlight conditions where poor estimation of even correctly specified models rules out empirical examination of isomorphism and homology without taking precautions, for instance, larger Level-2 sample sizes, or using informative priors. PMID:26973580

The spatial pattern of suicide in the US in relation to deprivation, fragmentation and rurality.

PubMed

Congdon, Peter

2011-01-01

Analysis of geographical patterns of suicide and psychiatric morbidity has demonstrated the impact of latent ecological variables (such as deprivation, rurality). Such latent variables may be derived by conventional multivariate techniques from sets of observed indices (for example, by principal components), by composite variable methods or by methods which explicitly consider the spatial framework of areas and, in particular, the spatial clustering of latent risks and outcomes. This article considers a latent random variable approach to explaining geographical contrasts in suicide in the US; and it develops a spatial structural equation model incorporating deprivation, social fragmentation and rurality. The approach allows for such latent spatial constructs to be correlated both within and between areas. Potential effects of area ethnic mix are also included. The model is applied to male and female suicide deaths over 2002–06 in 3142 US counties.

A Combined Molecular Dynamics and Experimental Study of Doped Polypyrrole.

PubMed

Fonner, John M; Schmidt, Christine E; Ren, Pengyu

2010-10-01

Polypyrrole (PPy) is a biocompatible, electrically conductive polymer that has great potential for battery, sensor, and neural implant applications. Its amorphous structure and insolubility, however, limit the experimental techniques available to study its structure and properties at the atomic level. Previous theoretical studies of PPy in bulk are also scarce. Using ab initio calculations, we have constructed a molecular mechanics force field of chloride-doped PPy (PPyCl) and undoped PPy. This model has been designed to integrate into the OPLS force field, and parameters are available for the Gromacs and TINKER software packages. Molecular dynamics (MD) simulations of bulk PPy and PPyCl have been performed using this force field, and the effects of chain packing and electrostatic scaling on the bulk polymer density have been investigated. The density of flotation of PPyCl films has been measured experimentally. Amorphous X-ray diffraction of PPyCl was obtained and correlated with atomic structures sampled from MD simulations. The force field reported here is foundational for bridging the gap between experimental measurements and theoretical calculations for PPy based materials.

Force field-dependent structural divergence revealed during long time simulations of Calbindin d9k.

PubMed

Project, Elad; Nachliel, Esther; Gutman, Menachem

2010-07-15

The structural and the dynamic features of the Calbindin (CaB) protein in its holo and apo states are compared using molecular dynamics simulations under nine different force fields (FFs) (G43a1, G53a6, Opls-AA, Amber94, Amber99, Amber99p, AmberGS, AmberGSs, and Amber99sb). The results show that most FFs reproduce reasonably well the majority of the experimentally derived features of the CaB protein. However, in several cases, there are significant differences in secondary structure properties, root mean square deviations (RMSDs), root mean square fluctuations (RMSFs), and S(2) order parameters among the various FFs. What is more, in certain cases, these parameters differed from the experimentally derived values. Some of these deviations became noticeable only after 50 ns. A comparison with experimental data indicates that, for CaB, the Amber94 shows overall best agreement with the measured values, whereas several others seem to deviate from both crystal and nuclear magnetic resonance data. Copyright 2009 Wiley Periodicals, Inc.

Topic Model for Graph Mining.

PubMed

Xuan, Junyu; Lu, Jie; Zhang, Guangquan; Luo, Xiangfeng

2015-12-01

Graph mining has been a popular research area because of its numerous application scenarios. Many unstructured and structured data can be represented as graphs, such as, documents, chemical molecular structures, and images. However, an issue in relation to current research on graphs is that they cannot adequately discover the topics hidden in graph-structured data which can be beneficial for both the unsupervised learning and supervised learning of the graphs. Although topic models have proved to be very successful in discovering latent topics, the standard topic models cannot be directly applied to graph-structured data due to the "bag-of-word" assumption. In this paper, an innovative graph topic model (GTM) is proposed to address this issue, which uses Bernoulli distributions to model the edges between nodes in a graph. It can, therefore, make the edges in a graph contribute to latent topic discovery and further improve the accuracy of the supervised and unsupervised learning of graphs. The experimental results on two different types of graph datasets show that the proposed GTM outperforms the latent Dirichlet allocation on classification by using the unveiled topics of these two models to represent graphs.

Latent topic discovery of clinical concepts from hospital discharge summaries of a heterogeneous patient cohort.

PubMed

Lehman, Li-Wei; Long, William; Saeed, Mohammed; Mark, Roger

2014-01-01

Patients in critical care often exhibit complex disease patterns. A fundamental challenge in clinical research is to identify clinical features that may be characteristic of adverse patient outcomes. In this work, we propose a data-driven approach for phenotype discovery of patients in critical care. We used Hierarchical Dirichlet Process (HDP) as a non-parametric topic modeling technique to automatically discover the latent "topic" structure of diseases, symptoms, and findings documented in hospital discharge summaries. We show that the latent topic structure can be used to reveal phenotypic patterns of diseases and symptoms shared across subgroups of a patient cohort, and may contain prognostic value in stratifying patients' post hospital discharge mortality risks. Using discharge summaries of a large patient cohort from the MIMIC II database, we evaluate the clinical utility of the discovered topic structure in identifying patients who are at high risk of mortality within one year post hospital discharge. We demonstrate that the learned topic structure has statistically significant associations with mortality post hospital discharge, and may provide valuable insights in defining new feature sets for predicting patient outcomes.

Latent Heating from TRMM Satellite Measurements

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Smith, E. A.; Adler, R.; Haddad, Z.; Hou, A.; Iguchi, T.; Kakar, R.; Krishnamurti, T.; Kummerow, C.; Lang, S.

2004-01-01

Rainfall production is the fundamental variable within the Earth's hydrological cycle because it is both the principal forcing term in surface water budgets and its energetics corollary, latent heating, is the principal source of atmospheric diabatic heating. Latent heat release itself is a consequence of phase changes between the vapor, liquid, and frozen states of water. The properties of the vertical distribution of latent heat release modulate large-scale meridional and zonal circulations within the tropics - as well as modifying the energetic efficiencies of midlatitude weather systems. This paper focuses on the retrieval of latent heat release from satellite measurements generated by the Tropical Rainfall Measuring Mission (TRMM) satellite observatory, which was launched in November 1997 as a joint American-Japanese space endeavor. Since then, TRMM measurements have been providing an accurate four-dimensional account of rainfall over the global tropics and sub-tropics, information which can be used to estimate the space-time structure of latent heating across the Earth's low latitudes. The paper examines how the observed TRMM distribution of rainfall has advanced an understanding of the global water and energy cycle and its consequent relationship to the atmospheric general circulation and climate via latent heat release. A set of algorithm methodologies that are being used to estimate latent heating based on rain rate retrievals from the TRMM observations are described. The characteristics of these algorithms and the latent heating products that can be generated from them are also described, along with validation analyses of the heating products themselves. Finally, the investigation provides an overview of how TRMM-derived latent heating information is currently being used in conjunction with global weather and climate models, concluding with remarks intended to stimulate further research on latent heating retrieval from satellites.

Latent Profile and Cluster Analysis of Infant Temperament: Comparisons across Person-Centered Approaches

ERIC Educational Resources Information Center

Gartstein, Maria A.; Prokasky, Amanda; Bell, Martha Ann; Calkins, Susan; Bridgett, David J.; Braungart-Rieker, Julia; Leerkes, Esther; Cheatham, Carol L.; Eiden, Rina D.; Mize, Krystal D.; Jones, Nancy Aaron; Mireault, Gina; Seamon, Erich

2017-01-01

There is renewed interest in person-centered approaches to understanding the structure of temperament. However, questions concerning temperament types are not frequently framed in a developmental context, especially during infancy. In addition, the most common person-centered techniques, cluster analysis (CA) and latent profile analysis (LPA),…

Applying the Mixed Rasch Model to the Runco Ideational Behavior Scale

ERIC Educational Resources Information Center

Sen, Sedat

2016-01-01

Previous research using creativity assessments has used latent class models and identified multiple classes (a 3-class solution) associated with various domains. This study explored the latent class structure of the Runco Ideational Behavior Scale, which was designed to quantify ideational capacity. A robust state-of the-art technique called the…

The Latent Classes of Subclinical ADHD Symptoms: Convergences of Multiple Informant Reports

ERIC Educational Resources Information Center

Kobor, Andrea; Takacs, Adam; Urban, Robert; Csepe, Valeria

2012-01-01

The purpose of the present study was to conduct latent class analysis on the Hyperactivity scale of the Strengths and Difficulties Questionnaire in order to identify distinct subgroups of subclinical ADHD in a multi-informant framework. We hypothesized a similar structure between teachers and parents, and differences in symptom severity across…

Comparing Latent Structures of the Grade of Membership, Rasch, and Latent Class Models

ERIC Educational Resources Information Center

Erosheva, Elena A.

2005-01-01

This paper focuses on model interpretation issues and employs a geometric approach to compare the potential value of using the Grade of Membership (GoM) model in representing population heterogeneity. We consider population heterogeneity manifolds generated by letting subject specific parameters vary over their natural range, while keeping other…

A Latent Variable Approach to Executive Control in Healthy Ageing

ERIC Educational Resources Information Center

Adrover-Roig, Daniel; Sese, Albert; Barcelo, Francisco; Palmer, Alfonso

2012-01-01

It is a well-established finding that the central executive is fractionated in at least three separable component processes: Updating, Shifting, and Inhibition of information (Miyake et al., 2000). However, the fractionation of the central executive among the elderly has been less well explored, and Miyake's et al. latent structure has not yet…

A Comparison of Methods for Estimating Quadratic Effects in Nonlinear Structural Equation Models

ERIC Educational Resources Information Center

Harring, Jeffrey R.; Weiss, Brandi A.; Hsu, Jui-Chen

2012-01-01

Two Monte Carlo simulations were performed to compare methods for estimating and testing hypotheses of quadratic effects in latent variable regression models. The methods considered in the current study were (a) a 2-stage moderated regression approach using latent variable scores, (b) an unconstrained product indicator approach, (c) a latent…

What If We Took Our Models Seriously? Estimating Latent Scores in Individuals

ERIC Educational Resources Information Center

Schneider, W. Joel

2013-01-01

Researchers often argue that the structural models of the constructs they study are relevant to clinicians. Unfortunately, few clinicians are able to translate the mathematically precise relationships between latent constructs and observed scores into information that can be usefully applied to individuals. Typically this means that when a new…

Mean structure analysis from an IRT approach: an application in the context of organizational psychology.

PubMed

Revuelta Menéndez, Javier; Ximénez Gómez, Carmen

2012-11-01

The application of mean and covariance structure analysis with quantitative data is increasing. However, latent means analysis with qualitative data is not as widespread. This article summarizes the procedures to conduct an analysis of latent means of dichotomous data from an item response theory approach. We illustrate the implementation of these procedures in an empirical example referring to the organizational context, where a multi-group analysis was conducted to compare the latent means of three employee groups in two factors measuring personal preferences and the perceived degree of rewards from the organization. Results show that higher personal motivations are associated with higher perceived importance of the organization, and that these perceptions differ across groups, so that higher-level employees have a lower level of personal and perceived motivation. The article shows how to estimate the factor means and the factor correlation from dichotomous data, and how to assess goodness of fit. Lastly, we provide the M-Plus syntax code in order to facilitate the latent means analyses for applied researchers.

Heating Structures Derived from Satellite

NASA Technical Reports Server (NTRS)

Tao, W.-K.; Adler, R.; Haddad, Z.; Hou, A.; Kakar, R.; Krishnamurti, T. N.; Kummerow, C.; Lang, S.; Meneghini, R.; Olson, W.

2004-01-01

Rainfall is a key link in the hydrologic cycle and is a primary heat source for the atmosphere. The vertical distribution of latent-heat release, which is accompanied by rainfall, modulates the large-scale circulations of the tropics and in turn can impact midlatitude weather. This latent heat release is a consequence of phase changes between vapor, liquid, and solid water. The Tropical Rainfall Measuring Mission (TRMM), a joint U.S./Japan space project, was launched in November 1997. It provides an accurate measurement of rainfall over the global tropics which can be used to estimate the four-dimensional structure of latent heating over the global tropics. The distributions of rainfall and inferred heating can be used to advance our understanding of the global energy and water cycle. This paper describes several different algorithms for estimating latent heating using TRMM observations. The strengths and weaknesses of each algorithm as well as the heating products are also discussed. The validation of heating products will be exhibited. Finally, the application of this heating information to global circulation and climate models is presented.

Phenotypic factor analysis of psychopathology reveals a new body-related transdiagnostic factor.

PubMed

Pezzoli, Patrizia; Antfolk, Jan; Santtila, Pekka

2017-01-01

Comorbidity challenges the notion of mental disorders as discrete categories. An increasing body of literature shows that symptoms cut across traditional diagnostic boundaries and interact in shaping the latent structure of psychopathology. Using exploratory and confirmatory factor analysis, we reveal the latent sources of covariation among nine measures of psychopathological functioning in a population-based sample of 13024 Finnish twins and their siblings. By implementing unidimensional, multidimensional, second-order, and bifactor models, we illustrate the relationships between observed variables, specific, and general latent factors. We also provide the first investigation to date of measurement invariance of the bifactor model of psychopathology across gender and age groups. Our main result is the identification of a distinct "Body" factor, alongside the previously identified Internalizing and Externalizing factors. We also report relevant cross-disorder associations, especially between body-related psychopathology and trait anger, as well as substantial sex and age differences in observed and latent means. The findings expand the meta-structure of psychopathology, with implications for empirical and clinical practice, and demonstrate shared mechanisms underlying attitudes towards nutrition, self-image, sexuality and anger, with gender- and age-specific features.

Spatial path models with multiple indicators and multiple causes: mental health in US counties.

PubMed

Congdon, Peter

2011-06-01

This paper considers a structural model for the impact on area mental health outcomes (poor mental health, suicide) of spatially structured latent constructs: deprivation, social capital, social fragmentation and rurality. These constructs are measured by multiple observed effect indicators, with the constructs allowed to be correlated both between and within areas. However, in the scheme developed here, particular latent constructs may also be influenced by known variables, or, via path sequences, by other constructs, possibly nonlinearly. For example, area social capital may be measured by effect indicators (e.g. associational density, charitable activity), but influenced as causes by other constructs (e.g. area deprivation), and by observed features of the socio-ethnic structure of areas. A model incorporating these features is applied to suicide mortality and the prevalence of poor mental health in 3141 US counties, which are related to the latent spatial constructs and to observed variables (e.g. county ethnic mix). Copyright © 2011 Elsevier Ltd. All rights reserved.

GARP regulates the bioavailability and activation of TGFβ.

PubMed

Wang, Rui; Zhu, Jianghai; Dong, Xianchi; Shi, Minlong; Lu, Chafen; Springer, Timothy A

2012-03-01

Glycoprotein-A repetitions predominant protein (GARP) associates with latent transforming growth factor-β (proTGFβ) on the surface of T regulatory cells and platelets; however, whether GARP functions in latent TGFβ activation and the structural basis of coassociation remain unknown. We find that Cys-192 and Cys-331 of GARP disulfide link to the TGFβ1 prodomain and that GARP with C192A and C331A mutations can also noncovalently associate with proTGFβ1. Noncovalent association is sufficiently strong for GARP to outcompete latent TGFβ-binding protein for binding to proTGFβ1. Association between GARP and proTGFβ1 prevents the secretion of TGFβ1. Integrin α(V)β(6) and to a lesser extent α(V)β(8) are able to activate TGFβ from the GARP-proTGFβ1 complex. Activation requires the RGD motif of latent TGFβ, disulfide linkage between GARP and latent TGFβ, and membrane association of GARP. Our results show that GARP is a latent TGFβ-binding protein that functions in regulating the bioavailability and activation of TGFβ.

Estimating Latent Variable Interactions With Non-Normal Observed Data: A Comparison of Four Approaches

PubMed Central

Cham, Heining; West, Stephen G.; Ma, Yue; Aiken, Leona S.

2012-01-01

A Monte Carlo simulation was conducted to investigate the robustness of four latent variable interaction modeling approaches (Constrained Product Indicator [CPI], Generalized Appended Product Indicator [GAPI], Unconstrained Product Indicator [UPI], and Latent Moderated Structural Equations [LMS]) under high degrees of non-normality of the observed exogenous variables. Results showed that the CPI and LMS approaches yielded biased estimates of the interaction effect when the exogenous variables were highly non-normal. When the violation of non-normality was not severe (normal; symmetric with excess kurtosis < 1), the LMS approach yielded the most efficient estimates of the latent interaction effect with the highest statistical power. In highly non-normal conditions, the GAPI and UPI approaches with ML estimation yielded unbiased latent interaction effect estimates, with acceptable actual Type-I error rates for both the Wald and likelihood ratio tests of interaction effect at N ≥ 500. An empirical example illustrated the use of the four approaches in testing a latent variable interaction between academic self-efficacy and positive family role models in the prediction of academic performance. PMID:23457417

A ricin forensic profiling approach based on a complex set of biomarkers.

PubMed

Fredriksson, Sten-Åke; Wunschel, David S; Lindström, Susanne Wiklund; Nilsson, Calle; Wahl, Karen; Åstot, Crister

2018-08-15

A forensic method for the retrospective determination of preparation methods used for illicit ricin toxin production was developed. The method was based on a complex set of biomarkers, including carbohydrates, fatty acids, seed storage proteins, in combination with data on ricin and Ricinus communis agglutinin. The analyses were performed on samples prepared from four castor bean plant (R. communis) cultivars by four different sample preparation methods (PM1-PM4) ranging from simple disintegration of the castor beans to multi-step preparation methods including different protein precipitation methods. Comprehensive analytical data was collected by use of a range of analytical methods and robust orthogonal partial least squares-discriminant analysis- models (OPLS-DA) were constructed based on the calibration set. By the use of a decision tree and two OPLS-DA models, the sample preparation methods of test set samples were determined. The model statistics of the two models were good and a 100% rate of correct predictions of the test set was achieved. Copyright © 2018 Elsevier B.V. All rights reserved.

A multivariate approach using attenuated total reflectance mid-infrared spectroscopy to measure the surface mannoproteins and β-glucans of yeast cell walls during wine fermentations.

PubMed

Moore, John P; Zhang, Song-Lei; Nieuwoudt, Hélène; Divol, Benoit; Trygg, Johan; Bauer, Florian F

2015-11-18

Yeast cells possess a cell wall comprising primarily glycoproteins, mannans, and glucan polymers. Several yeast phenotypes relevant for fermentation, wine processing, and wine quality are correlated with cell wall properties. To investigate the effect of wine fermentation on cell wall composition, a study was performed using mid-infrared (MIR) spectroscopy coupled with multivariate methods (i.e., PCA and OPLS-DA). A total of 40 yeast strains were evaluated, including Saccharomyces strains (laboratory and industrial) and non-Saccharomyces species. Cells were fermented in both synthetic MS300 and Chardonnay grape must to stationery phase, processed, and scanned in the MIR spectrum. PCA of the fingerprint spectral region showed distinct separation of Saccharomyces strains from non-Saccharomyces species; furthermore, industrial wine yeast strains separated from laboratory strains. PCA loading plots and the use of OPLS-DA to the data sets suggested that industrial strains were enriched with cell wall proteins (e.g., mannoproteins), whereas laboratory strains were composed mainly of mannan and glucan polymers.

Optimal study design with identical power: an application of power equivalence to latent growth curve models.

PubMed

von Oertzen, Timo; Brandmaier, Andreas M

2013-06-01

Structural equation models have become a broadly applied data-analytic framework. Among them, latent growth curve models have become a standard method in longitudinal research. However, researchers often rely solely on rules of thumb about statistical power in their study designs. The theory of power equivalence provides an analytical answer to the question of how design factors, for example, the number of observed indicators and the number of time points assessed in repeated measures, trade off against each other while holding the power for likelihood-ratio tests on the latent structure constant. In this article, we present applications of power-equivalent transformations on a model with data from a previously published study on cognitive aging, and highlight consequences of participant attrition on power. PsycINFO Database Record (c) 2013 APA, all rights reserved.

The computational nature of memory modification.

PubMed

Gershman, Samuel J; Monfils, Marie-H; Norman, Kenneth A; Niv, Yael

2017-03-15

Retrieving a memory can modify its influence on subsequent behavior. We develop a computational theory of memory modification, according to which modification of a memory trace occurs through classical associative learning, but which memory trace is eligible for modification depends on a structure learning mechanism that discovers the units of association by segmenting the stream of experience into statistically distinct clusters (latent causes). New memories are formed when the structure learning mechanism infers that a new latent cause underlies current sensory observations. By the same token, old memories are modified when old and new sensory observations are inferred to have been generated by the same latent cause. We derive this framework from probabilistic principles, and present a computational implementation. Simulations demonstrate that our model can reproduce the major experimental findings from studies of memory modification in the Pavlovian conditioning literature.

The Latent Class Structure of Chinese Patients with Eating Disorders in Shanghai.

PubMed

Zheng, Yuchen; Kang, Qing; Huang, Jiabin; Jiang, Wenhui; Liu, Qiang; Chen, Han; Fan, Qing; Wang, Zhen; Chen, Jue; Xiao, Zeping

2017-08-25

Eating disorder is culture related, and the clinical symptoms are different between eastern and western patients. So the validity of feeding and eating disorders in the upcoming ICD-11 guide for Chinese patients is unclear. To explore the latent class structure of Chinese patients with eating disorder and the cross-cultural validity of the eating disorder section of the new ICD-11 guide in China. A total of 379 patients with eating disorders at Shanghai Mental Health Center were evaluated using the EDI questionnaire and a questionnaire developed by researchers from 2010 to 2016. SPSS 20.0 was used to enter data and analyze demographic data, and Latent GOLD was employed to conduct latent profile analysis. According to the results of latent profile analysis, patients with eating disorder were divided into five classes: low-weight fasting class (23.1%), non-fat-phobic binge/purge class (21.54%), low-fat-phobic binge class (19.27%), fat-phobic binge class (19.27%), and non-fat-phobic low-weight class (16.76%). Among the clinical symptoms extracted, there were significant differences in Body Mass Index (BMI), binge eating behavior, self-induced vomiting, laxative use and fat-phobic opinion; while there was no significant difference in restrictive food intake. Based on the clinical symptoms, there are five latent classes in Chinese patients with eating disorder, which is in accordance with the diagnostic categories of feeding and eating disorder in ICD-11. However, further work is needed in improving the fat-phobic opinion of patients with eating disorder and clarifying the BMI standard of thinness in the Chinese population.

Latent transition models with latent class predictors: attention deficit hyperactivity disorder subtypes and high school marijuana use

PubMed Central

Reboussin, Beth A.; Ialongo, Nicholas S.

2011-01-01

Summary Attention deficit hyperactivity disorder (ADHD) is a neurodevelopmental disorder which is most often diagnosed in childhood with symptoms often persisting into adulthood. Elevated rates of substance use disorders have been evidenced among those with ADHD, but recent research focusing on the relationship between subtypes of ADHD and specific drugs is inconsistent. We propose a latent transition model (LTM) to guide our understanding of how drug use progresses, in particular marijuana use, while accounting for the measurement error that is often found in self-reported substance use data. We extend the LTM to include a latent class predictor to represent empirically derived ADHD subtypes that do not rely on meeting specific diagnostic criteria. We begin by fitting two separate latent class analysis (LCA) models by using second-order estimating equations: a longitudinal LCA model to define stages of marijuana use, and a cross-sectional LCA model to define ADHD subtypes. The LTM model parameters describing the probability of transitioning between the LCA-defined stages of marijuana use and the influence of the LCA-defined ADHD subtypes on these transition rates are then estimated by using a set of first-order estimating equations given the LCA parameter estimates. A robust estimate of the LTM parameter variance that accounts for the variation due to the estimation of the two sets of LCA parameters is proposed. Solving three sets of estimating equations enables us to determine the underlying latent class structures independently of the model for the transition rates and simplifying assumptions about the correlation structure at each stage reduces the computational complexity. PMID:21461139

Biomedical Applications of Mid-Infrared Spectroscopic Imaging and Multivariate Data Analysis: Contribution to the Understanding of Diabetes Pathogenesis

NASA Astrophysics Data System (ADS)

Aboualizadeh, Ebrahim

Diabetic retinopathy (DR) is a microvascular complication of diabetes and a leading cause of adult vision loss. Although a great deal of progress has been made in ophthalmological examinations and clinical approaches to detect the signs of retinopathy in patients with diabetes, there still remain outstanding questions regarding the molecular and biochemical changes involved. To discover the biochemical mechanisms underlying the development and progression of changes in the retina as a result of diabetes, a more comprehensive understanding of the bio-molecular processes, in individual retinal cells subjected to hyperglycemia, is required. Animal models provide a suitable resource for temporal detection of the underlying pathophysiological and biochemical changes associated with DR, which is not fully attainable in human studies. In the present study, I aimed to determine the nature of diabetes-induced, highly localized biochemical changes in the retinal tissue from Ins2Akita/+ (Akita/+; a model of Type I diabetes) male mice with different duration of diabetes. Employing label-free, spatially resolved Fourier transform infrared (FT-IR) imaging engaged with chemometric tools enabled me to identify temporal-dependent reproducible biomarkers of the diabetic retinal tissue from mice with 6 or 12 weeks, and 6 or 10 months of diabetes. I report, for the first time, the origin of molecular changes in the biochemistry of individual retinal layers with different duration of diabetes. A robust classification between distinctive retinal layers - namely photoreceptor layer (PRL), outer plexiform layer (OPL), inner nuclear layer (INL), and inner plexiform layer (IPL) - and associated temporal-dependent spectral biomarkers, were delineated. Spatially-resolved super resolution chemical images revealed oxidative stress-induced structural and morphological alterations within the nucleus of the photoreceptors. Comparison among the PRL, OPL, INL, and IPL suggested that the photoreceptor layer is the most susceptible layer to the oxidative stress with short-duration of diabetes. Moreover, for the first time, we present the temporal-dependent molecular alterations for the PRL, OPL, INL, and IPL from Akita/+ mice, with progression of diabetes. These findings are potentially important and may be of particular benefit in understanding the molecular and biological activity of retinal cells during oxidative stress in diabetes. Our integrating paradigm provides a new conceptual framework and a significant rationale for a better understanding of the molecular and cellular mechanisms underlying the development and progression of DR. This approach may yield alternative and potentially complimentary methods for the assessment of diabetes changes. It is expected that the conclusions drawn from this work will bridge the gap in our knowledge regarding the biochemical mechanisms of the DR and address some critical needs in the biomedical community.

Structural identifiability of cyclic graphical models of biological networks with latent variables.

PubMed

Wang, Yulin; Lu, Na; Miao, Hongyu

2016-06-13

Graphical models have long been used to describe biological networks for a variety of important tasks such as the determination of key biological parameters, and the structure of graphical model ultimately determines whether such unknown parameters can be unambiguously obtained from experimental observations (i.e., the identifiability problem). Limited by resources or technical capacities, complex biological networks are usually partially observed in experiment, which thus introduces latent variables into the corresponding graphical models. A number of previous studies have tackled the parameter identifiability problem for graphical models such as linear structural equation models (SEMs) with or without latent variables. However, the limited resolution and efficiency of existing approaches necessarily calls for further development of novel structural identifiability analysis algorithms. An efficient structural identifiability analysis algorithm is developed in this study for a broad range of network structures. The proposed method adopts the Wright's path coefficient method to generate identifiability equations in forms of symbolic polynomials, and then converts these symbolic equations to binary matrices (called identifiability matrix). Several matrix operations are introduced for identifiability matrix reduction with system equivalency maintained. Based on the reduced identifiability matrices, the structural identifiability of each parameter is determined. A number of benchmark models are used to verify the validity of the proposed approach. Finally, the network module for influenza A virus replication is employed as a real example to illustrate the application of the proposed approach in practice. The proposed approach can deal with cyclic networks with latent variables. The key advantage is that it intentionally avoids symbolic computation and is thus highly efficient. Also, this method is capable of determining the identifiability of each single parameter and is thus of higher resolution in comparison with many existing approaches. Overall, this study provides a basis for systematic examination and refinement of graphical models of biological networks from the identifiability point of view, and it has a significant potential to be extended to more complex network structures or high-dimensional systems.

Classification and Short-Term Course of DSM-IV Cannabis, Hallucinogen, Cocaine, and Opioid Disorders in Treated Adolescents

ERIC Educational Resources Information Center

Chung, Tammy; Martin, Christoper S.

2005-01-01

This study examined the latent class structure of Diagnostic and Statistical Manual of Mental Disorders (text rev.; DSM-IV; American Psychiatric Association, 2000) symptoms used to diagnose cannabis, hallucinogen, cocaine, and opiate disorders among 501 adolescents recruited from addictions treatment. Latent class results were compared with the…

Multilevel Latent Class Analysis: An Application of Adolescent Smoking Typologies with Individual and Contextual Predictors

ERIC Educational Resources Information Center

Henry, Kimberly L.; Muthen, Bengt

2010-01-01

Latent class analysis (LCA) is a statistical method used to identify subtypes of related cases using a set of categorical or continuous observed variables. Traditional LCA assumes that observations are independent. However, multilevel data structures are common in social and behavioral research and alternative strategies are needed. In this…

Two-Year Predictive Validity of Conduct Disorder Subtypes in Early Adolescence: A Latent Class Analysis of a Canadian Longitudinal Sample

ERIC Educational Resources Information Center

Lacourse, Eric; Baillargeon, Raymond; Dupere, Veronique; Vitaro, Frank; Romano, Elisa; Tremblay, Richard

2010-01-01

Background: Investigating the latent structure of conduct disorder (CD) can help clarify how symptoms related to aggression, property destruction, theft, and serious violations of rules cluster in individuals with this disorder. Discovering homogeneous subtypes can be useful for etiologic, treatment, and prevention purposes depending on the…

A Note on the Specification of Error Structures in Latent Interaction Models

ERIC Educational Resources Information Center

Mao, Xiulin; Harring, Jeffrey R.; Hancock, Gregory R.

2015-01-01

Latent interaction models have motivated a great deal of methodological research, mainly in the area of estimating such models. Product-indicator methods have been shown to be competitive with other methods of estimation in terms of parameter bias and standard error accuracy, and their continued popularity in empirical studies is due, in part, to…

The Benefits of Latent Variable Modeling to Develop Norms for a Translated Version of a Standardized Scale

ERIC Educational Resources Information Center

Seo, Hyojeong; Shaw, Leslie A.; Shogren, Karrie A.; Lang, Kyle M.; Little, Todd D.

2017-01-01

This article demonstrates the use of structural equation modeling to develop norms for a translated version of a standardized scale, the Supports Intensity Scale-Children's Version (SIS-C). The latent variable norming method proposed is useful when the standardization sample for a translated version is relatively small to derive norms…

Positive Adult Support and Depression Symptoms in Adolescent Females: The Partially Mediating Role of Eating Disturbances

ERIC Educational Resources Information Center

Linville, Deanna; O'Neil, Maya; Huebner, Angela

2011-01-01

This study examined linkages between depression symptoms (DEP) and positive adult support (PAS) in female adolescents and the partially mediating influence of eating disturbances (ED). Structural equation modeling was used to establish measurement models for each of the latent constructs, determine the relationships among the latent constructs,…

Measurement Equivalence of Teachers' Sense of Efficacy Scale Using Latent Growth Methods

ERIC Educational Resources Information Center

Basokçu, T. Oguz; Ögretmen, T.

2016-01-01

This study is based on the application of latent growth modeling, which is one of structural equation models on real data. Teachers' Sense of Efficacy Scale (TSES), which was previously adapted into Turkish was administered to 200 preservice teachers at different time intervals for three times and study data was collected. Measurement equivalence…

The Structure of Student Satisfaction with College Services: A Latent Class Model

ERIC Educational Resources Information Center

Adwere-Boamah, Joseph

2011-01-01

Latent Class Analysis (LCA) was used to identify distinct groups of Community college students based on their self-ratings of satisfaction with student service programs. The programs were counseling, financial aid, health center, student programs and student government. The best fitting model to describe the data was a two Discrete-Factor model…

Latent Variable Regression 4-Level Hierarchical Model Using Multisite Multiple-Cohorts Longitudinal Data. CRESST Report 801

ERIC Educational Resources Information Center

Choi, Kilchan

2011-01-01

This report explores a new latent variable regression 4-level hierarchical model for monitoring school performance over time using multisite multiple-cohorts longitudinal data. This kind of data set has a 4-level hierarchical structure: time-series observation nested within students who are nested within different cohorts of students. These…

Unfinished Business in Clarifying Causal Measurement: Commentary on Bainter and Bollen

ERIC Educational Resources Information Center

Markus, Keith A.

2014-01-01

In a series of articles and comments, Kenneth Bollen and his collaborators have incrementally refined an account of structural equation models that (a) model a latent variable as the effect of several observed variables and (b) carry an interpretation of the observed variables as, in some sense, measures of the latent variable that they cause.…

Generalized reduced rank latent factor regression for high dimensional tensor fields, and neuroimaging-genetic applications

PubMed Central

Tao, Chenyang; Nichols, Thomas E.; Hua, Xue; Ching, Christopher R.K.; Rolls, Edmund T.; Thompson, Paul M.; Feng, Jianfeng

2017-01-01

We propose a generalized reduced rank latent factor regression model (GRRLF) for the analysis of tensor field responses and high dimensional covariates. The model is motivated by the need from imaging-genetic studies to identify genetic variants that are associated with brain imaging phenotypes, often in the form of high dimensional tensor fields. GRRLF identifies from the structure in the data the effective dimensionality of the data, and then jointly performs dimension reduction of the covariates, dynamic identification of latent factors, and nonparametric estimation of both covariate and latent response fields. After accounting for the latent and covariate effects, GRLLF performs a nonparametric test on the remaining factor of interest. GRRLF provides a better factorization of the signals compared with common solutions, and is less susceptible to overfitting because it exploits the effective dimensionality. The generality and the flexibility of GRRLF also allow various statistical models to be handled in a unified framework and solutions can be efficiently computed. Within the field of neuroimaging, it improves the sensitivity for weak signals and is a promising alternative to existing approaches. The operation of the framework is demonstrated with both synthetic datasets and a real-world neuroimaging example in which the effects of a set of genes on the structure of the brain at the voxel level were measured, and the results compared favorably with those from existing approaches. PMID:27666385

Evaluating Force Fields for the Computational Prediction of Ionized Arginine and Lysine Side-Chains Partitioning into Lipid Bilayers and Octanol.

PubMed

Sun, Delin; Forsman, Jan; Woodward, Clifford E

2015-04-14

Abundant peptides and proteins containing arginine (Arg) and lysine (Lys) amino acids can apparently permeate cell membranes with ease. However, the mechanisms by which these peptides and proteins succeed in traversing the free energy barrier imposed by cell membranes remain largely unestablished. Precise thermodynamic studies (both theoretical and experimental) on the interactions of Arg and Lys residues with model lipid bilayers can provide valuable clues to the efficacy of these cationic peptides and proteins. We have carried out molecular dynamics simulations to calculate the interactions of ionized Arg and Lys side-chains with the zwitterionic 1,2-dipalmitoyl-sn-glycero-3-phosphocholine (DPPC) lipid bilayer for 10 widely used lipid/protein force fields: CHARMM36/CHARMM36, SLIPID/AMBER99SB-ILDN, OPLS-AA/OPLS-AA, Berger/OPLS-AA, Berger/GROMOS87, Berger/GROMOS53A6, GROMOS53A6/GROMOS53A6, nonpolarizable MARTINI, polarizable MARTINI, and BMW MARTINI. We performed umbrella sampling simulations to obtain the potential of mean force for Arg and Lys side-chains partitioning from water to the bilayer interior. We found significant differences between the force fields, both for the interactions between side-chains and bilayer surface, as well as the free energy cost for placing the side-chain at the center of the bilayer. These simulation results were compared with the Wimley-White interfacial scale. We also calculated the free energy cost for transferring ionized Arg and Lys side-chains from water to both dry and wet octanol. Our simulations reveal rapid diffusion of water molecules into octanol whereby the equilibrium mole fraction of water in the wet octanol phase was ∼25%. Surprisingly, our free energy calculations found that the high water content in wet octanol lowered the water-to-octanol partitioning free energies for cationic residues by only 0.6 to 0.7 kcal/mol.

Remote sensing image segmentation using local sparse structure constrained latent low rank representation

NASA Astrophysics Data System (ADS)

Tian, Shu; Zhang, Ye; Yan, Yimin; Su, Nan; Zhang, Junping

2016-09-01

Latent low-rank representation (LatLRR) has been attached considerable attention in the field of remote sensing image segmentation, due to its effectiveness in exploring the multiple subspace structures of data. However, the increasingly heterogeneous texture information in the high spatial resolution remote sensing images, leads to more severe interference of pixels in local neighborhood, and the LatLRR fails to capture the local complex structure information. Therefore, we present a local sparse structure constrainted latent low-rank representation (LSSLatLRR) segmentation method, which explicitly imposes the local sparse structure constraint on LatLRR to capture the intrinsic local structure in manifold structure feature subspaces. The whole segmentation framework can be viewed as two stages in cascade. In the first stage, we use the local histogram transform to extract the texture local histogram features (LHOG) at each pixel, which can efficiently capture the complex and micro-texture pattern. In the second stage, a local sparse structure (LSS) formulation is established on LHOG, which aims to preserve the local intrinsic structure and enhance the relationship between pixels having similar local characteristics. Meanwhile, by integrating the LSS and the LatLRR, we can efficiently capture the local sparse and low-rank structure in the mixture of feature subspace, and we adopt the subspace segmentation method to improve the segmentation accuracy. Experimental results on the remote sensing images with different spatial resolution show that, compared with three state-of-the-art image segmentation methods, the proposed method achieves more accurate segmentation results.

Latent change models of adult cognition: are changes in processing speed and working memory associated with changes in episodic memory?

PubMed

Hertzog, Christopher; Dixon, Roger A; Hultsch, David F; MacDonald, Stuart W S

2003-12-01

The authors used 6-year longitudinal data from the Victoria Longitudinal Study (VLS) to investigate individual differences in amount of episodic memory change. Latent change models revealed reliable individual differences in cognitive change. Changes in episodic memory were significantly correlated with changes in other cognitive variables, including speed and working memory. A structural equation model for the latent change scores showed that changes in speed and working memory predicted changes in episodic memory, as expected by processing resource theory. However, these effects were best modeled as being mediated by changes in induction and fact retrieval. Dissociations were detected between cross-sectional ability correlations and longitudinal changes. Shuffling the tasks used to define the Working Memory latent variable altered patterns of change correlations.

Understanding comorbidity among internalizing problems: Integrating latent structural models of psychopathology and risk mechanisms

PubMed Central

Hankin, Benjamin L.; Snyder, Hannah R.; Gulley, Lauren D.; Schweizer, Tina H.; Bijttebier, Patricia; Nelis, Sabine; Toh, Gim; Vasey, Michael W.

2016-01-01

It is well known that comorbidity is the rule, not the exception, for categorically defined psychiatric disorders, and this is also the case for internalizing disorders of depression and anxiety. This theoretical review paper addresses the ubiquity of comorbidity among internalizing disorders. Our central thesis is that progress in understanding this co-occurrence can be made by employing latent dimensional structural models that organize both psychopathology as well as vulnerabilities and risk mechanisms and by connecting the multiple levels of risk and psychopathology outcomes together. Different vulnerabilities and risk mechanisms are hypothesized to predict different levels of the structural model of psychopathology. We review the present state of knowledge based on concurrent and developmental sequential comorbidity patterns among common discrete psychiatric disorders in youth, and then we advocate for the use of more recent bifactor dimensional models of psychopathology (e.g., p factor, Caspi et al., 2014) that can help to explain the co-occurrence among internalizing symptoms. In support of this relatively novel conceptual perspective, we review six exemplar vulnerabilities and risk mechanisms, including executive function, information processing biases, cognitive vulnerabilities, positive and negative affectivity aspects of temperament, and autonomic dysregulation, along with the developmental occurrence of stressors in different domains, to show how these vulnerabilities can predict the general latent psychopathology factor, a unique latent internalizing dimension, as well as specific symptom syndrome manifestations. PMID:27739389

Structural Equation Model Trees

PubMed Central

Brandmaier, Andreas M.; von Oertzen, Timo; McArdle, John J.; Lindenberger, Ulman

2015-01-01

In the behavioral and social sciences, structural equation models (SEMs) have become widely accepted as a modeling tool for the relation between latent and observed variables. SEMs can be seen as a unification of several multivariate analysis techniques. SEM Trees combine the strengths of SEMs and the decision tree paradigm by building tree structures that separate a data set recursively into subsets with significantly different parameter estimates in a SEM. SEM Trees provide means for finding covariates and covariate interactions that predict differences in structural parameters in observed as well as in latent space and facilitate theory-guided exploration of empirical data. We describe the methodology, discuss theoretical and practical implications, and demonstrate applications to a factor model and a linear growth curve model. PMID:22984789

The latent structure of the functional dyspepsia symptom complex: a taxometric analysis.

PubMed

Van Oudenhove, L; Jasper, F; Walentynowicz, M; Witthöft, M; Van den Bergh, O; Tack, J

2016-07-01

Rome III introduced a subdivision of functional dyspepsia (FD) into postprandial distress syndrome and epigastric pain syndrome, characterized by early satiation/postprandial fullness, and epigastric pain/burning, respectively. However, evidence on their degree of overlap is mixed. We aimed to investigate the latent structure of FD to test whether distinguishable symptom-based subgroups exist. Consecutive tertiary care Rome II FD patients completed the dyspepsia symptom severity scale. Confirmatory factor analysis (CFA) was used to compare the fit of a single factor model, a correlated three-factor model based on Rome III subgroups and a bifactor model consisting of a general FD factor and orthogonal subgroup factors. Taxometric analyses were subsequently used to investigate the latent structure of FD. Nine hundred and fifty-seven FD patients (71.1% women, age 41 ± 14.8) participated. In CFA, the bifactor model yielded a significantly better fit than the two other models (χ² difference tests both p < 0.001). All symptoms had significant loadings on both the general and the subgroup-specific factors (all p < 0.05). Somatization was associated with the general (r = 0.72, p < 0.01), but not the subgroup-specific factors (all r < 0.13, p > 0.05). Taxometric analyses supported a dimensional structure of FD (all CCFI<0.38). We found a dimensional rather than categorical latent structure of the FD symptom complex in tertiary care. A combination of a general dyspepsia symptom reporting factor, which was associated with somatization, and symptom-specific factors reflecting the Rome III subdivision fitted the data best. This has implications for classification, pathophysiology, and treatment of FD. © 2016 John Wiley & Sons Ltd.

Psychometrican analysis and dimensional structure of the Brazilian version of melasma quality of life scale (MELASQoL-BP)*

PubMed Central

Maranzatto, Camila Fernandes Pollo; Miot, Hélio Amante; Miot, Luciane Donida Bartoli; Meneguin, Silmara

2016-01-01

Background Although asymptomatic, melasma inflicts significant impact on quality of life. MELASQoL is the main instrument used to assess quality of life associated with melasma, it has been validated in several languages, but its latent dimensional structure and psychometric properties haven´t been fully explored. Objectives To evaluate psychometric characteristics, information and dimensional structure of the Brazilian version of MELASQoL. Methods Survey with patients with facial melasma through socio-demographic questionnaire, DLQI-BRA, MASI and MELASQoL-BP, exploratory and confirmatory factor analysis, internal consistency of MELASQoL and latent dimensions (Cronbach's alpha). The informativeness of the model and items were investigated by the Rasch model (ordinal data). Results We evaluated 154 patients, 134 (87%) were female, mean age (± SD) of 39 (± 8) years, the onset of melasma at 27 (± 8) years, median (p25-p75) of MASI scores , DLQI and MELASQoL 8 (5-15) 2 (1-6) and 30 (17-44). The correlation (rho) of MELASQoL with DLQI and MASI were: 0.70 and 0.36. Exploratory factor analysis identified two latent dimensions: Q1-Q3 and Q4-Q10, which had significantly more adjusted factor structure than the one-dimensional model: Χ2 / gl = 2.03, CFI = 0.95, AGFI = 0.94, RMSEA = 0.08. Cronbach's coefficient for the one-dimensional model and the factors were: 0.95, 0.92 and 0.93. Rasch analysis demonstrated that the use of seven alternatives per item resulted in no increase in the model informativeness. Conclusions MELASQoL-BP showed good psychometric performance and a latent structure of two dimensions. We also identified an oversizing of item alternatives to characterize the aggregate information to each dimension. PMID:27579735

The computational nature of memory modification

PubMed Central

Gershman, Samuel J; Monfils, Marie-H; Norman, Kenneth A; Niv, Yael

2017-01-01

Retrieving a memory can modify its influence on subsequent behavior. We develop a computational theory of memory modification, according to which modification of a memory trace occurs through classical associative learning, but which memory trace is eligible for modification depends on a structure learning mechanism that discovers the units of association by segmenting the stream of experience into statistically distinct clusters (latent causes). New memories are formed when the structure learning mechanism infers that a new latent cause underlies current sensory observations. By the same token, old memories are modified when old and new sensory observations are inferred to have been generated by the same latent cause. We derive this framework from probabilistic principles, and present a computational implementation. Simulations demonstrate that our model can reproduce the major experimental findings from studies of memory modification in the Pavlovian conditioning literature. DOI: http://dx.doi.org/10.7554/eLife.23763.001 PMID:28294944

Many-level multilevel structural equation modeling: An efficient evaluation strategy.

PubMed

Pritikin, Joshua N; Hunter, Michael D; von Oertzen, Timo; Brick, Timothy R; Boker, Steven M

2017-01-01

Structural equation models are increasingly used for clustered or multilevel data in cases where mixed regression is too inflexible. However, when there are many levels of nesting, these models can become difficult to estimate. We introduce a novel evaluation strategy, Rampart, that applies an orthogonal rotation to the parts of a model that conform to commonly met requirements. This rotation dramatically simplifies fit evaluation in a way that becomes more potent as the size of the data set increases. We validate and evaluate the implementation using a 3-level latent regression simulation study. Then we analyze data from a state-wide child behavioral health measure administered by the Oklahoma Department of Human Services. We demonstrate the efficiency of Rampart compared to other similar software using a latent factor model with a 5-level decomposition of latent variance. Rampart is implemented in OpenMx, a free and open source software.

The Coach-Athlete Relationship Questionnaire (CART-Q): development and initial validation.

PubMed

Jowett, Sophia; Ntoumanis, Nikos

2004-08-01

The purpose of the present study was to develop and validate a self-report instrument that measures the nature of the coach-athlete relationship. Jowett et al.'s (Jowett & Meek, 2000; Jowett, in press) qualitative case studies and relevant literature were used to generate items for an instrument that measures affective, cognitive, and behavioral aspects of the coach-athlete relationship. Two studies were carried out in an attempt to assess content, predictive, and construct validity, as well as internal consistency, of the Coach-Athlete Relationship Questionnaire (CART-Q), using two independent British samples. Principal component analysis and confirmatory factor analysis were used to reduce the number of items, identify principal components, and confirm the latent structure of the CART-Q. Results supported the multidimensional nature of the coach-athlete relationship. The latent structure of the CART-Q was underlined by the latent variables of coaches' and athletes' Closeness (emotions), Commitment (cognitions), and Complementarity (behaviors).

Measurement Invariance and Latent Mean Differences in the Reynolds Intellectual Assessment Scales (RIAS): Does the German Version of the RIAS Allow a Valid Assessment of Individuals with a Migration Background?

PubMed Central

Gygi, Jasmin T.; Fux, Elodie; Grob, Alexander; Hagmann-von Arx, Priska

2016-01-01

This study examined measurement invariance and latent mean differences in the German version of the Reynolds Intellectual Assessment Scales (RIAS) for 316 individuals with a migration background (defined as speaking German as a second language) and 316 sex- and age-matched natives. The RIAS measures general intelligence (single-factor structure) and its two components, verbal and nonverbal intelligence (two-factor structure). Results of a multi-group confirmatory factor analysis showed scalar invariance for the two-factor and partial scalar invariance for the single-factor structure. We conclude that the two-factor structure of the RIAS is comparable across groups. Hence, verbal and nonverbal intelligence but not general intelligence should be considered when comparing RIAS test results of individuals with and without a migration background. Further, latent mean differences especially on the verbal, but also on the nonverbal intelligence index indicate language barriers for individuals with a migration background, as subtests corresponding to verbal intelligence require higher skills in German language. Moreover, cultural, environmental, and social factors that have to be taken into account when assessing individuals with a migration background are discussed. PMID:27846270

LATENT SPACE MODELS FOR MULTIVIEW NETWORK DATA

PubMed Central

Salter-Townshend, Michael; McCormick, Tyler H.

2018-01-01

Social relationships consist of interactions along multiple dimensions. In social networks, this means that individuals form multiple types of relationships with the same person (e.g., an individual will not trust all of his/her acquaintances). Statistical models for these data require understanding two related types of dependence structure: (i) structure within each relationship type, or network view, and (ii) the association between views. In this paper, we propose a statistical framework that parsimoniously represents dependence between relationship types while also maintaining enough flexibility to allow individuals to serve different roles in different relationship types. Our approach builds on work on latent space models for networks [see, e.g., J. Amer. Statist. Assoc. 97 (2002) 1090–1098]. These models represent the propensity for two individuals to form edges as conditionally independent given the distance between the individuals in an unobserved social space. Our work departs from previous work in this area by representing dependence structure between network views through a multivariate Bernoulli likelihood, providing a representation of between-view association. This approach infers correlations between views not explained by the latent space model. Using our method, we explore 6 multiview network structures across 75 villages in rural southern Karnataka, India [Banerjee et al. (2013)]. PMID:29721127

LATENT SPACE MODELS FOR MULTIVIEW NETWORK DATA.

PubMed

Salter-Townshend, Michael; McCormick, Tyler H

2017-09-01

Social relationships consist of interactions along multiple dimensions. In social networks, this means that individuals form multiple types of relationships with the same person (e.g., an individual will not trust all of his/her acquaintances). Statistical models for these data require understanding two related types of dependence structure: (i) structure within each relationship type, or network view, and (ii) the association between views. In this paper, we propose a statistical framework that parsimoniously represents dependence between relationship types while also maintaining enough flexibility to allow individuals to serve different roles in different relationship types. Our approach builds on work on latent space models for networks [see, e.g., J. Amer. Statist. Assoc. 97 (2002) 1090-1098]. These models represent the propensity for two individuals to form edges as conditionally independent given the distance between the individuals in an unobserved social space. Our work departs from previous work in this area by representing dependence structure between network views through a multivariate Bernoulli likelihood, providing a representation of between-view association. This approach infers correlations between views not explained by the latent space model. Using our method, we explore 6 multiview network structures across 75 villages in rural southern Karnataka, India [Banerjee et al. (2013)].

On the Benefits of Latent Variable Modeling for Norming Scales: The Case of the "Supports Intensity Scale-Children's Version"

ERIC Educational Resources Information Center

Seo, Hyojeong; Little, Todd D.; Shogren, Karrie A.; Lang, Kyle M.

2016-01-01

Structural equation modeling (SEM) is a powerful and flexible analytic tool to model latent constructs and their relations with observed variables and other constructs. SEM applications offer advantages over classical models in dealing with statistical assumptions and in adjusting for measurement error. So far, however, SEM has not been fully used…

Matrix completion by deep matrix factorization.

PubMed

Fan, Jicong; Cheng, Jieyu

2018-02-01

Conventional methods of matrix completion are linear methods that are not effective in handling data of nonlinear structures. Recently a few researchers attempted to incorporate nonlinear techniques into matrix completion but there still exists considerable limitations. In this paper, a novel method called deep matrix factorization (DMF) is proposed for nonlinear matrix completion. Different from conventional matrix completion methods that are based on linear latent variable models, DMF is on the basis of a nonlinear latent variable model. DMF is formulated as a deep-structure neural network, in which the inputs are the low-dimensional unknown latent variables and the outputs are the partially observed variables. In DMF, the inputs and the parameters of the multilayer neural network are simultaneously optimized to minimize the reconstruction errors for the observed entries. Then the missing entries can be readily recovered by propagating the latent variables to the output layer. DMF is compared with state-of-the-art methods of linear and nonlinear matrix completion in the tasks of toy matrix completion, image inpainting and collaborative filtering. The experimental results verify that DMF is able to provide higher matrix completion accuracy than existing methods do and DMF is applicable to large matrices. Copyright © 2017 Elsevier Ltd. All rights reserved.

General practitioners' knowledge and concern about electromagnetic fields.

PubMed

Berg-Beckhoff, Gabriele; Breckenkamp, Jürgen; Larsen, Pia Veldt; Kowall, Bernd

2014-12-01

Our aim is to explore general practitioners' (GPs') knowledge about EMF, and to assess whether different knowledge structures are related to the GPs' concern about EMF. Random samples were drawn from lists of GPs in Germany in 2008. Knowledge about EMF was assessed by seven items. A latent class analysis was conducted to identify latent structures in GPs' knowledge. Further, the GPs' concern about EMF health risk was measured using a score comprising six items. The association between GPs' concern about EMF and their knowledge was analysed using multiple linear regression. In total 435 (response rate 23.3%) GPs participated in the study. Four groups were identified by the latent class analysis: 43.1% of the GPs gave mainly correct answers; 23.7% of the GPs answered low frequency EMF questions correctly; 19.2% answered only the questions relating EMF with health risks, and 14.0% answered mostly "don't know". There was no association between GPs' latent knowledge classes or between the number of correct answers given by the GPs and their EMF concern, whereas the number of incorrect answers was associated with EMF concern. Greater EMF concern in subjects with more incorrect answers suggests paying particular attention to misconceptions regarding EMF in risk communication.

Demographic analysis from summaries of an age-structured population

USGS Publications Warehouse

Link, William A.; Royle, J. Andrew; Hatfield, Jeff S.

2003-01-01

Demographic analyses of age-structured populations typically rely on life history data for individuals, or when individual animals are not identified, on information about the numbers of individuals in each age class through time. While it is usually difficult to determine the age class of a randomly encountered individual, it is often the case that the individual can be readily and reliably assigned to one of a set of age classes. For example, it is often possible to distinguish first-year from older birds. In such cases, the population age structure can be regarded as a latent variable governed by a process prior, and the data as summaries of this latent structure. In this article, we consider the problem of uncovering the latent structure and estimating process parameters from summaries of age class information. We present a demographic analysis for the critically endangered migratory population of whooping cranes (Grus americana), based only on counts of first-year birds and of older birds. We estimate age and year-specific survival rates. We address the controversial issue of whether management action on the breeding grounds has influenced recruitment, relating recruitment rates to the number of seventh-year and older birds, and examining the pattern of variation through time in this rate.

Transcriptional regulation of latent feline immunodeficiency virus in peripheral CD4+ T-lymphocytes.

PubMed

McDonnel, Samantha J; Sparger, Ellen E; Luciw, Paul A; Murphy, Brian G

2012-05-01

Feline immunodeficiency virus (FIV), the lentivirus of domestic cats responsible for feline AIDS, establishes a latent infection in peripheral blood CD4+ T-cells approximately eight months after experimental inoculation. In this study, cats experimentally infected with the FIV-C strain in the asymptomatic phase demonstrated an estimated viral load of 1 infected cell per approximately 10(3) CD4+ T-cells, with about 1 copy of viral DNA per cell. Approximately 1 in 10 proviral copies was capable of transcription in the asymptomatic phase. The latent FIV proviral promoter was associated with deacetylated, methylated histones, which is consistent with a condensed chromatin structure. In contrast, the transcriptionally active FIV promoter was associated with histone acetylation and demethylation. In addition, RNA polymerase II appeared to be paused on the latent viral promoter, and short promoter-proximal transcripts were detected. Our findings for the FIV promoter in infected cats are similar to results obtained in studies of human immunodeficiency virus (HIV)-1 latent proviruses in cell culture in vitro studies. Thus, the FIV/cat model may offer insights into in vivo mechanisms of HIV latency and provides a unique opportunity to test novel therapeutic interventions aimed at eradicating latent virus.

Clinical Insight Into Latent Variables of Psychiatric Questionnaires for Mood Symptom Self-Assessment

PubMed Central

Saunders, Kate; Bilderbeck, Amy; Palmius, Niclas; Goodwin, Guy; De Vos, Maarten

2017-01-01

Background We recently described a new questionnaire to monitor mood called mood zoom (MZ). MZ comprises 6 items assessing mood symptoms on a 7-point Likert scale; we had previously used standard principal component analysis (PCA) to tentatively understand its properties, but the presence of multiple nonzero loadings obstructed the interpretation of its latent variables. Objective The aim of this study was to rigorously investigate the internal properties and latent variables of MZ using an algorithmic approach which may lead to more interpretable results than PCA. Additionally, we explored three other widely used psychiatric questionnaires to investigate latent variable structure similarities with MZ: (1) Altman self-rating mania scale (ASRM), assessing mania; (2) quick inventory of depressive symptomatology (QIDS) self-report, assessing depression; and (3) generalized anxiety disorder (7-item) (GAD-7), assessing anxiety. Methods We elicited responses from 131 participants: 48 bipolar disorder (BD), 32 borderline personality disorder (BPD), and 51 healthy controls (HC), collected longitudinally (median [interquartile range, IQR]: 363 [276] days). Participants were requested to complete ASRM, QIDS, and GAD-7 weekly (all 3 questionnaires were completed on the Web) and MZ daily (using a custom-based smartphone app). We applied sparse PCA (SPCA) to determine the latent variables for the four questionnaires, where a small subset of the original items contributes toward each latent variable. Results We found that MZ had great consistency across the three cohorts studied. Three main principal components were derived using SPCA, which can be tentatively interpreted as (1) anxiety and sadness, (2) positive affect, and (3) irritability. The MZ principal component comprising anxiety and sadness explains most of the variance in BD and BPD, whereas the positive affect of MZ explains most of the variance in HC. The latent variables in ASRM were identical for the patient groups but different for HC; nevertheless, the latent variables shared common items across both the patient group and HC. On the contrary, QIDS had overall very different principal components across groups; sleep was a key element in HC and BD but was absent in BPD. In GAD-7, nervousness was the principal component explaining most of the variance in BD and HC. Conclusions This study has important implications for understanding self-reported mood. MZ has a consistent, intuitively interpretable latent variable structure and hence may be a good instrument for generic mood assessment. Irritability appears to be the key distinguishing latent variable between BD and BPD and might be useful for differential diagnosis. Anxiety and sadness are closely interlinked, a finding that might inform treatment effects to jointly address these covarying symptoms. Anxiety and nervousness appear to be amongst the cardinal latent variable symptoms in BD and merit close attention in clinical practice. PMID:28546141

Elucidating the association between the self-harm inventory and several borderline personality measures in an inpatient psychiatric sample.

PubMed

Sellbom, Martin; Sansone, Randy A; Songer, Douglas A

2017-09-01

The current study evaluated the utility of the self-harm inventory (SHI) as a proxy for and screening measure of borderline personality disorder (BPD) using several diagnostic and statistical manual of mental disorders (DSM)-based BPD measures as criteria. We used a sample of 145 psychiatric inpatients, who completed the SHI and a series of well-validated, DSM-based self-report measures of BPD. Using a series of latent trait and latent class analyses, we found that the SHI was substantially associated with a latent construct representing BPD, as well as differentiated latent classes of 'high' vs. 'low' BPD, with good accuracy. The SHI can serve as proxy for and a good screening measure for BPD, but future research needs to replicate these findings using structured interview-based measurement of BPD.

Latent Growth and Dynamic Structural Equation Models.

PubMed

Grimm, Kevin J; Ram, Nilam

2018-05-07

Latent growth models make up a class of methods to study within-person change-how it progresses, how it differs across individuals, what are its determinants, and what are its consequences. Latent growth methods have been applied in many domains to examine average and differential responses to interventions and treatments. In this review, we introduce the growth modeling approach to studying change by presenting different models of change and interpretations of their model parameters. We then apply these methods to examining sex differences in the development of binge drinking behavior through adolescence and into adulthood. Advances in growth modeling methods are then discussed and include inherently nonlinear growth models, derivative specification of growth models, and latent change score models to study stochastic change processes. We conclude with relevant design issues of longitudinal studies and considerations for the analysis of longitudinal data.

Multilevel Dynamic Generalized Structured Component Analysis for Brain Connectivity Analysis in Functional Neuroimaging Data.

PubMed

Jung, Kwanghee; Takane, Yoshio; Hwang, Heungsun; Woodward, Todd S

2016-06-01

We extend dynamic generalized structured component analysis (GSCA) to enhance its data-analytic capability in structural equation modeling of multi-subject time series data. Time series data of multiple subjects are typically hierarchically structured, where time points are nested within subjects who are in turn nested within a group. The proposed approach, named multilevel dynamic GSCA, accommodates the nested structure in time series data. Explicitly taking the nested structure into account, the proposed method allows investigating subject-wise variability of the loadings and path coefficients by looking at the variance estimates of the corresponding random effects, as well as fixed loadings between observed and latent variables and fixed path coefficients between latent variables. We demonstrate the effectiveness of the proposed approach by applying the method to the multi-subject functional neuroimaging data for brain connectivity analysis, where time series data-level measurements are nested within subjects.

On the Benefits of Latent Variable Modeling for Norming Scales: The Case of the "Supports Intensity Scale--Children's Version"

ERIC Educational Resources Information Center

Seo, Hyojeong; Little, Todd D.; Shogren, Karrie A.; Lang, Kyle M.

2016-01-01

Structural equation modeling (SEM) is a powerful and flexible analytic tool to model latent constructs and their relations with observed variables and other constructs. SEM applications offer advantages over classical models in dealing with statistical assumptions and in adjusting for measurement error. So far, however, SEM has not been fully used…

Direct and conceptual replications of the taxometric analysis of type a behavior.

PubMed

Wilmot, Michael P; Haslam, Nick; Tian, Jingyuan; Ones, Deniz S

2018-05-17

We present direct and conceptual replications of the influential taxometric analysis of Type A Behavior (TAB; Strube, 1989), which reported evidence for the latent typology of the construct. Study 1, the direct replication (N = 2,373), duplicated sampling and methodological procedures of the original study, but results showed that the item indicators used in the original study lacked sufficient validity to unambiguously determine latent structure. Using improved factorial subscale indicators to further test the question, multiple taxometric procedures, in combination with parallel analyses of simulated data, failed to replicate the original typological finding. Study 2, the conceptual replication, tested the latent structure of the wider construct of TAB using the sample from the Caerphilly Prospective Study (N = 2,254), which contains responses to the three most widely used self-report measures of TAB: the Jenkins Activity Survey, Bortner scale, and Framingham scale. Factorial subscale indicators were derived from the measures and submitted to multiple taxometric procedures. Results of Study 2 converged with those of Study 1, providing clear evidence of latent dimensional structure. Overall, results suggest there is no evidence for the type in TAB. Findings imply that theoretical models of TAB, assessment practices, and data analytic procedures that assume a typology should be replaced by dimensional models, factorial subscale measures, and corresponding statistical approaches. Specific subscale measures that tap multiple Big Five trait domains, and show evidence of predictive utility, are also recommended. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

An isolate of Potato Virus X capsid protein from N. benthamiana: Insights from homology modeling and molecular dynamics simulation.

PubMed

Esfandiari, Neda; Sefidbakht, Yahya

2018-05-17

Since Potato Virus X (PVX) is easily transmitted mechanically between their hosts, its control is difficult. We have previously reported new isolate of this virus (PVX-Iran, GenBank Accession number FJ461343). However, the molecular basis of resistance breaking activity and its relation to capsid protein structure are still not well-understood. SDS-PAGE, ELISA, Western blot and RT-PCR molecular examinations were performed on the inoculated plants Nicotiana benthamiana. The pathological symptoms were related to the PVX isolate. The capsid protein (CP) structure were modeled based on homology and subjected to three independent 80 ns molecular dynamics minimization (GROMACS, OPLS force field) in the SPC water box. The RMSD, RMSF, SASA, and electrostatic properties were retrieved from the trajectories. Flexibility and hydrophilic nature of the N-terminal residues (1-34) of solvated CP could be observed in conformational changes upon minimization. The obtained structure was then docked with NbPCIP1 using ClusPro 2.0. The strong binding affinity of these two proteins (≈-16.0 Kcal mol -1 ) represents the formation of inclusion body and hence appearance of the symptoms. Copyright © 2018 Elsevier B.V. All rights reserved.

Representing Heterogeneity in Structural Relationships Among Multiple Choice Variables Using a Latent Segmentation Approach

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

Garikapati, Venu; Astroza, Sebastian; Pendyala, Ram M.

Travel model systems often adopt a single decision structure that links several activity-travel choices together. The single decision structure is then used to predict activity-travel choices, with those downstream in the decision-making chain influenced by those upstream in the sequence. The adoption of a singular sequential causal structure to depict relationships among activity-travel choices in travel demand model systems ignores the possibility that some choices are made jointly as a bundle as well as the possible presence of structural heterogeneity in the population with respect to decision-making processes. As different segments in the population may adopt and follow different causalmore » decision-making mechanisms when making selected choices jointly, it would be of value to develop simultaneous equations model systems relating multiple endogenous choice variables that are able to identify population subgroups following alternative causal decision structures. Because the segments are not known a priori, they are considered latent and determined endogenously within a joint modeling framework proposed in this paper. The methodology is applied to a national mobility survey data set to identify population segments that follow different causal structures relating residential location choice, vehicle ownership, and car-share and mobility service usage. It is found that the model revealing three distinct latent segments best describes the data, confirming the efficacy of the modeling approach and the existence of structural heterogeneity in decision-making in the population. Future versions of activity-travel model systems should strive to incorporate such structural heterogeneity to better reflect varying decision processes across population subgroups.« less

Effect of oxygen on volatile and sensory characteristics of Cabernet Sauvignon during secondary shelf life.

PubMed

Lee, Dong-Hyun; Kang, Bo-Sik; Park, Hyun-Jin

2011-11-09

The oxidation of Cabernet Sauvignon wines during secondary shelf life was studied by headspace solid-phase microextraction (HS-SPME) coupled to gas chromatography-quadrupole mass spectrometry (GC-qMS) and sensory tests, with the support of multivariate statistical analyses such as OPLS-DA loading plot and PCA score plot. Four different oxidation conditions were established during a 1-week secondary shelf life. Samples collected on a regular basis were analyzed to determine the changes of volatile chemicals, with sensory characteristics evaluated through pattern recognition models. During secondary shelf life the separation among collected samples depended on the degree of oxidation in wine. Isoamyl acetate, ethyl decanoate, nonanoic acid, n-decanoic acid, undecanoic acid, 2-furancarboxylic acid, dodecanoic acid, and phenylacetaldehyde were determined to be associated with the oxidation of the wine. PCA sensory evaluation revealed that least oxidized wine and fresh wine was well-separated from more oxidized wines, demonstrating that sensory characteristics of less oxidized wines tend toward "fruity", "citrous", and "sweetness", while those of more oxidized wines are positively correlated with "animal", "bitterness", and "dairy". The study also demonstrates that OPLS-DA and PCA are very useful statistical tools for the understanding of wine oxidation.

Impairment of photoreceptor ribbon synapses in a novel Pomt1 conditional knockout mouse model of dystroglycanopathy.

PubMed

Rubio-Fernández, Marcos; Uribe, Mary Luz; Vicente-Tejedor, Javier; Germain, Francisco; Susín-Lara, Cristina; Quereda, Cristina; Montoliu, Lluis; de la Villa, Pedro; Martín-Nieto, José; Cruces, Jesús

2018-06-04

Hypoglycosylation of α-dystroglycan (α-DG) resulting from deficiency of protein O-mannosyltransferase 1 (POMT1) may cause severe neuromuscular dystrophies with brain and eye anomalies, named dystroglycanopathies. The retinal involvement of these disorders motivated us to generate a conditional knockout (cKO) mouse experiencing a Pomt1 intragenic deletion (exons 3-4) during the development of photoreceptors, mediated by the Cre recombinase expressed from the cone-rod homeobox (Crx) gene promoter. In this mouse, retinal α-DG was unglycosylated and incapable of binding laminin. Retinal POMT1 deficiency caused significant impairments in both electroretinographic recordings and optokinetic reflex in Pomt1 cKO mice, and immunohistochemical analyses revealed the absence of β-DG and of the α-DG-interacting protein, pikachurin, in the outer plexiform layer (OPL). At the ultrastructural level, noticeable alterations were observed in the ribbon synapses established between photoreceptors and bipolar cells. Therefore, O-mannosylation of α-DG in the retina carried out by POMT1 is crucial for the establishment of proper synapses at the OPL and transmission of visual information from cones and rods to their postsynaptic neurons.

The role of steroids in the prediction of affective disorders in adult men.

PubMed

Šrámková, Monika; Dušková, Michaela; Hill, Martin; Bičíková, Marie; Řípová, Daniela; Mohr, Pavel; Stárka, Luboslav

2017-05-01

Anxiety and mood disorders (AMD) are the most frequent mental disorders in the human population. They have recently shown increasing prevalence, and commonly disrupt personal and working lives. The aim of our study was to analyze the spectrum of circulating steroids in order to discover differences that could potentially be markers of affective depression or anxiety, and identify which steroids could be a predictive component for these diseases. We studied the steroid metabolome including 47 analytes in 20 men with depression (group D), 20 men with anxiety (group AN) and 30 healthy controls. OPLS and multivariate regression models were used for statistical analysis. Discrimination of group D from controls by the OPLS method was absolute, as was group AN from controls (sensitivity=1.000 (0.839, 1.000), specificity=1.000 (0.887, 1.000)). Relatively good predictivity was also found for discrimination between group D from AN (sensitivity=0.850 (0.640, 0.948), specificity=0.900 (0.699, 0.972)). Selected circulating steroids, including those that are neuroactive and neuroprotective, can be useful tools for discriminating between these affective diseases in adult men. Copyright © 2016. Published by Elsevier Inc.

Multivariate analysis of PRISMA optimized TLC image for predicting antioxidant activity and identification of contributing compounds from Pereskia bleo.

PubMed

Sharif, K M; Rahman, M M; Azmir, J; Khatib, A; Sabina, E; Shamsudin, S H; Zaidul, I S M

2015-12-01

Multivariate analysis of thin-layer chromatography (TLC) images was modeled to predict antioxidant activity of Pereskia bleo leaves and to identify the contributing compounds of the activity. TLC was developed in optimized mobile phase using the 'PRISMA' optimization method and the image was then converted to wavelet signals and imported for multivariate analysis. An orthogonal partial least square (OPLS) model was developed consisting of a wavelet-converted TLC image and 2,2-diphynyl-picrylhydrazyl free radical scavenging activity of 24 different preparations of P. bleo as the x- and y-variables, respectively. The quality of the constructed OPLS model (1 + 1 + 0) with one predictive and one orthogonal component was evaluated by internal and external validity tests. The validated model was then used to identify the contributing spot from the TLC plate that was then analyzed by GC-MS after trimethylsilyl derivatization. Glycerol and amine compounds were mainly found to contribute to the antioxidant activity of the sample. An alternative method to predict the antioxidant activity of a new sample of P. bleo leaves has been developed. Copyright © 2015 John Wiley & Sons, Ltd.

Stellate nonhereditary idiopathic foveomacular retinoschisis concomitant to exudative maculopathies

PubMed Central

Casalino, G; Upendran, M; Bandello, F; Chakravarthy, U

2016-01-01

Purpose To report the clinical course of patients presenting with stellate nonhereditary idiopathic foveomacular retinoschisis (SNIFR) concomitant with exudative maculopathies. Methods Retrospective case series. Multimodal imaging findings, including spectral-domain optical coherence tomography (SD-OCT) were reviewed. Genetic testing for the RS1 gene was performed in one patient. Results We identified two female patients who fit the definition of SNIFR and presented with concomitant neovascular age-related macular degeneration (n-AMD). In both the patients, SD-OCT showed exudative macular features and splitting (bilateral in patient 1, unilateral in patient 2) of the outer plexiform layer (OPL) in the macula with no other evidence of hereditary or an acquired predisposing condition. Genetic testing excluded mutation of RS1 gene in patient 1. The fundi of both the patients showed characteristic signs of active choroidal neovascularization (CNV) and following anti-VEGF treatment, visual acuity improved and CNV-related exudative changes resolved. However, the split along the OPL remained unaltered. Conclusions SNIFR may be associated with n-AMD. It is important to recognise the presence of retinoschisis when there is other exudative pathology as the former may be misinterpreted as intraretinal fluid, prompting unnecessary treatment. PMID:26915743

Combining Coarse-Grained Protein Models with Replica-Exchange All-Atom Molecular Dynamics

PubMed Central

Wabik, Jacek; Kmiecik, Sebastian; Gront, Dominik; Kouza, Maksim; Koliński, Andrzej

2013-01-01

We describe a combination of all-atom simulations with CABS, a well-established coarse-grained protein modeling tool, into a single multiscale protocol. The simulation method has been tested on the C-terminal beta hairpin of protein G, a model system of protein folding. After reconstructing atomistic details, conformations derived from the CABS simulation were subjected to replica-exchange molecular dynamics simulations with OPLS-AA and AMBER99sb force fields in explicit solvent. Such a combination accelerates system convergence several times in comparison with all-atom simulations starting from the extended chain conformation, demonstrated by the analysis of melting curves, the number of native-like conformations as a function of time and secondary structure propagation. The results strongly suggest that the proposed multiscale method could be an efficient and accurate tool for high-resolution studies of protein folding dynamics in larger systems. PMID:23665897

Realist identification of group-level latent variables for perinatal social epidemiology theory building.

PubMed

Eastwood, John Graeme; Jalaludin, Bin Badrudin; Kemp, Lynn Ann; Phung, Hai Ngoc

2014-01-01

We have previously reported in this journal on an ecological study of perinatal depressive symptoms in South Western Sydney. In that article, we briefly reported on a factor analysis that was utilized to identify empirical indicators for analysis. In this article, we report on the mixed method approach that was used to identify those latent variables. Social epidemiology has been slow to embrace a latent variable approach to the study of social, political, economic, and cultural structures and mechanisms, partly for philosophical reasons. Critical realist ontology and epistemology have been advocated as an appropriate methodological approach to both theory building and theory testing in the health sciences. We describe here an emergent mixed method approach that uses qualitative methods to identify latent constructs followed by factor analysis using empirical indicators chosen to measure identified qualitative codes. Comparative analysis of the findings is reported together with a limited description of realist approaches to abstract reasoning.

Nonlinear Structured Growth Mixture Models in Mplus and OpenMx

PubMed Central

Grimm, Kevin J.; Ram, Nilam; Estabrook, Ryne

2014-01-01

Growth mixture models (GMMs; Muthén & Muthén, 2000; Muthén & Shedden, 1999) are a combination of latent curve models (LCMs) and finite mixture models to examine the existence of latent classes that follow distinct developmental patterns. GMMs are often fit with linear, latent basis, multiphase, or polynomial change models because of their common use, flexibility in modeling many types of change patterns, the availability of statistical programs to fit such models, and the ease of programming. In this paper, we present additional ways of modeling nonlinear change patterns with GMMs. Specifically, we show how LCMs that follow specific nonlinear functions can be extended to examine the presence of multiple latent classes using the Mplus and OpenMx computer programs. These models are fit to longitudinal reading data from the Early Childhood Longitudinal Study-Kindergarten Cohort to illustrate their use. PMID:25419006

Constraints of recreational sport participation: measurement invariance and latent mean differences across sex and physical activity status.

PubMed

Liu, Jing Dong; Chung, Pak Kwong; Chen, Wing Ping

2014-10-01

The purpose of the current study was to (a) examine the measurement invariance of the Constraint Scale of Sport Participation across sex and physical activity status among the undergraduate students (N = 630) in Hong Kong and (b) compare the latent mean differences across groups. Measurement invariance of the Constraint Scale of Sport Participation across sex of and physical activity status of the participants was examined first. With receiving support on the measurement invariance across groups, latent mean differences of the scores across groups were examined. Multi-group confirmatory factor analysis revealed that the configural, metric, scalar, and structural invariance of the scale was supported across groups. The results of latent mean differences suggested that the women reported significantly higher constraints on time, partner, psychology, knowledge, and interest than the men. The physically inactive participants reported significantly higher scores on all constraints except for accessibility than the physically active participants.

Replicates in high dimensions, with applications to latent variable graphical models.

PubMed

Tan, Kean Ming; Ning, Yang; Witten, Daniela M; Liu, Han

2016-12-01

In classical statistics, much thought has been put into experimental design and data collection. In the high-dimensional setting, however, experimental design has been less of a focus. In this paper, we stress the importance of collecting multiple replicates for each subject in this setting. We consider learning the structure of a graphical model with latent variables, under the assumption that these variables take a constant value across replicates within each subject. By collecting multiple replicates for each subject, we are able to estimate the conditional dependence relationships among the observed variables given the latent variables. To test the null hypothesis of conditional independence between two observed variables, we propose a pairwise decorrelated score test. Theoretical guarantees are established for parameter estimation and for this test. We show that our proposal is able to estimate latent variable graphical models more accurately than some existing proposals, and apply the proposed method to a brain imaging dataset.

Estimation of the latent mediated effect with ordinal data using the limited-information and Bayesian full-information approaches.

PubMed

Chen, Jinsong; Zhang, Dake; Choi, Jaehwa

2015-12-01

It is common to encounter latent variables with ordinal data in social or behavioral research. Although a mediated effect of latent variables (latent mediated effect, or LME) with ordinal data may appear to be a straightforward combination of LME with continuous data and latent variables with ordinal data, the methodological challenges to combine the two are not trivial. This research covers model structures as complex as LME and formulates both point and interval estimates of LME for ordinal data using the Bayesian full-information approach. We also combine weighted least squares (WLS) estimation with the bias-corrected bootstrapping (BCB; Efron Journal of the American Statistical Association, 82, 171-185, 1987) method or the traditional delta method as the limited-information approach. We evaluated the viability of these different approaches across various conditions through simulation studies, and provide an empirical example to illustrate the approaches. We found that the Bayesian approach with reasonably informative priors is preferred when both point and interval estimates are of interest and the sample size is 200 or above.

Laboratory test of a novel structural model of anxiety sensitivity and panic vulnerability.

PubMed

Bernstein, Amit; Zvolensky, Michael J; Zvolensky, Michael J; Schmidt, Norman B

2009-06-01

The current study evaluated a novel latent structural model of anxiety sensitivity (AS) in relation to panic vulnerability among a sample of young adults (N=216). AS was measured using the 16-item Anxiety Sensitivity Index (ASI; Reiss, Peterson, Gursky, & McNally, 1986), and panic vulnerability was indexed by panic attack responding to a single administration of a 4-minute, 10% CO(2) challenge. As predicted, vulnerability for panic attack responding to biological challenge was associated with dichotomous individual differences between taxonic AS classes and continuous within-taxon class individual differences in AS physical concerns. Findings supported the AS taxonic-dimensional hypothesis of AS latent structure and panic vulnerability. These findings are discussed in terms of their theoretical and clinical implications.

Factorial Invariance and Latent Mean Differences of Scores on the Achievement Goal Tendencies Questionnaire across Gender and Age in a Sample of Spanish Students

ERIC Educational Resources Information Center

Ingles, Candido J.; Marzo, Juan C.; Castejon, Juan L.; Nunez, Jose Carlos; Valle, Antonio; Garcia-Fernandez, Jose M.; Delgado, Beatriz

2011-01-01

This study examined the factorial invariance and latent mean differences of scores on the Spanish version of the "Achievement Goal Tendencies Questionnaire" (AGTQ) across gender and age groups in 2022 Spanish students (51.1% boys) in grades 7 through 10. The equality of factor structures was compared using multi-group confirmatory factor…

Analyzing latent state-trait and multiple-indicator latent growth curve models as multilevel structural equation models

PubMed Central

Geiser, Christian; Bishop, Jacob; Lockhart, Ginger; Shiffman, Saul; Grenard, Jerry L.

2013-01-01

Latent state-trait (LST) and latent growth curve (LGC) models are frequently used in the analysis of longitudinal data. Although it is well-known that standard single-indicator LGC models can be analyzed within either the structural equation modeling (SEM) or multilevel (ML; hierarchical linear modeling) frameworks, few researchers realize that LST and multivariate LGC models, which use multiple indicators at each time point, can also be specified as ML models. In the present paper, we demonstrate that using the ML-SEM rather than the SL-SEM framework to estimate the parameters of these models can be practical when the study involves (1) a large number of time points, (2) individually-varying times of observation, (3) unequally spaced time intervals, and/or (4) incomplete data. Despite the practical advantages of the ML-SEM approach under these circumstances, there are also some limitations that researchers should consider. We present an application to an ecological momentary assessment study (N = 158 youths with an average of 23.49 observations of positive mood per person) using the software Mplus (Muthén and Muthén, 1998–2012) and discuss advantages and disadvantages of using the ML-SEM approach to estimate the parameters of LST and multiple-indicator LGC models. PMID:24416023

Latent Variable Modeling of Brain Gray Matter Volume and Psychopathy in Incarcerated Offenders

PubMed Central

Baskin-Sommers, Arielle R.; Neumann, Craig S.; Cope, Lora M.; Kiehl, Kent A.

2016-01-01

Advanced statistical modeling has become a prominent feature in psychological science and can be a useful approach for representing the neural architecture linked to psychopathology. Psychopathy, a disorder characterized by dysfunction in interpersonal-affective and impulsive-antisocial domains, is associated with widespread neural abnormalities. Several imaging studies suggest that underlying structural deficits in paralimbic regions are associated with psychopathy. While these studies are useful, they make assumptions about the organization of the brain and its relevance to individuals displaying psychopathic features. Capitalizing on statistical modeling, the present study (N=254) used latent variable methods to examine the structure of gray matter volume in male offenders, and assessed the latent relations between psychopathy and gray matter factors reflecting paralimbic and non-paralimbic regions. Results revealed good fit for a four-factor gray matter paralimbic model and these first-order factors were accounted for by a super-ordinate paralimbic ‘system’ factor. Moreover, a super-ordinate psychopathy factor significantly predicted the paralimbic, but not the non-paralimbic factor. The latent variable paralimbic model, specifically linked with psychopathy, goes beyond understanding of single brain regions within the system and provides evidence for psychopathy-related gray matter volume reductions in the paralimbic system as a whole. PMID:27269123

Plus and minus RNAs of peach latent mosaic viroid self-cleave in vitro via hammerhead structures.

PubMed Central

Hernández, C; Flores, R

1992-01-01

Peach latent mosaic viroid (PLMVd), the causal agent of peach latent mosaic disease, has been sequenced and found to be a circular RNA molecule of 337 nucleotide residues, which adopts a branched conformation when it is folded in the model of lowest free energy. PLMVd exhibits limited homologies with other viroids and some satellite RNAs, but it does not have any of the central conserved sequences characteristic of the subgroups of typical viroids. However, a segment of approximately one-third of the PLMVd sequence has the elements required to form in the RNAs of both polarities the hammerhead structures proposed to act in the in vitro self-cleavage of avocado sunblotch viroid (ASBVd) and some satellite RNAs. Plus and minus partial- and full-length RNA transcripts of PLMVd containing the hammerhead structures displayed self-cleavage during transcription and after purification as predicted by these structures. These data are consistent with the high stability of the PLMVd hammerhead structures, more similar to the corresponding structures of some satellite RNAs than to those of ASBVd, and indicate that the self-cleavage reactions of PLMVd are most probably mediated by single hammerhead structures. Our results support the inclusion of PLMVd in a viroid subgroup represented by ASBVd, whose members are characterized by their ability to self-cleave in vitro, and probably in vivo, through hammerhead structures. A consensus phylogenetic tree has been obtained suggesting that PLMVd, together with ASBVd, may represent an evolutionary link between viroids and viroid-like satellite RNAs. Images PMID:1373888

Discontinuous Patterns of Cigarette Smoking From Ages 18 to 50 in the United States: A Repeated-Measures Latent Class Analysis.

PubMed

Terry-McElrath, Yvonne M; O'Malley, Patrick M; Johnston, Lloyd D

2017-12-13

Effective cigarette smoking prevention and intervention programming is enhanced by accurate understanding of developmental smoking pathways across the life span. This study investigated within-person patterns of cigarette smoking from ages 18 to 50 among a US national sample of high school graduates, focusing on identifying ages of particular importance for smoking involvement change. Using data from approximately 15,000 individuals participating in the longitudinal Monitoring the Future study, trichotomous measures of past 30-day smoking obtained at 11 time points were modeled using repeated-measures latent class analyses. Sex differences in latent class structure and membership were examined. Twelve latent classes were identified: three characterized by consistent smoking patterns across age (no smoking; smoking < pack per day; smoking pack + per day); three showing uptake to a higher category of smoking across age; four reflecting successful quit behavior by age 50; and two defined by discontinuous shifts between smoking categories. The same latent class structure was found for both males and females, but membership probabilities differed between sexes. Although evidence of increases or decreases in smoking behavior was observed at virtually all ages through 35, 21/22 and 29/30 appeared to be particularly key for smoking category change within class. This examination of latent classes of cigarette smoking among a national US longitudinal sample of high school graduates from ages 18 to 50 identified unique patterns and critical ages of susceptibility to change in smoking category within class. Such information may be of particular use in developing effective smoking prevention and intervention programming. This study examined cigarette smoking among a national longitudinal US sample of high school graduates from ages 18 to 50 and identified distinct latent classes characterized by patterns of movement between no cigarette use, light-to-moderate smoking, and the conventional definition of heavy smoking at 11 time points via repeated-measures latent class analysis. Membership probabilities for each smoking class were estimated, and critical ages of susceptibility to change in smoking behaviors were identified. © The Author 2017. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Generalized Multilevel Structural Equation Modeling

ERIC Educational Resources Information Center

Rabe-Hesketh, Sophia; Skrondal, Anders; Pickles, Andrew

2004-01-01

A unifying framework for generalized multilevel structural equation modeling is introduced. The models in the framework, called generalized linear latent and mixed models (GLLAMM), combine features of generalized linear mixed models (GLMM) and structural equation models (SEM) and consist of a response model and a structural model for the latent…

Do gamblers eat more salt? Testing a latent trait model of covariance in consumption

PubMed Central

Goodwin, Belinda C.; Browne, Matthew; Rockloff, Matthew; Donaldson, Phillip

2015-01-01

A diverse class of stimuli, including certain foods, substances, media, and economic behaviours, may be described as ‘reward-oriented’ in that they provide immediate reinforcement with little initial investment. Neurophysiological and personality concepts, including dopaminergic dysfunction, reward sensitivity and rash impulsivity, each predict the existence of a latent behavioural trait that leads to increased consumption of all stimuli in this class. Whilst bivariate relationships (co-morbidities) are often reported in the literature, to our knowledge, a multivariate investigation of this possible trait has not been done. We surveyed 1,194 participants (550 male) on their typical weekly consumption of 11 types of reward-oriented stimuli, including fast food, salt, caffeine, television, gambling products, and illicit drugs. Confirmatory factor analysis was used to compare models in a 3×3 structure, based on the definition of a single latent factor (none, fixed loadings, or estimated loadings), and assumed residual covariance structure (none, a-priori / literature based, or post-hoc / data-driven). The inclusion of a single latent behavioural ‘consumption’ factor significantly improved model fit in all cases. Also confirming theoretical predictions, estimated factor loadings on reward-oriented indicators were uniformly positive, regardless of assumptions regarding residual covariances. Additionally, the latent trait was found to be negatively correlated with the non-reward-oriented indicators of fruit and vegetable consumption. The findings support the notion of a single behavioural trait leading to increased consumption of reward-oriented stimuli across multiple modalities. We discuss implications regarding the concentration of negative lifestyle-related health behaviours. PMID:26551907

pong: fast analysis and visualization of latent clusters in population genetic data.

PubMed

Behr, Aaron A; Liu, Katherine Z; Liu-Fang, Gracie; Nakka, Priyanka; Ramachandran, Sohini

2016-09-15

A series of methods in population genetics use multilocus genotype data to assign individuals membership in latent clusters. These methods belong to a broad class of mixed-membership models, such as latent Dirichlet allocation used to analyze text corpora. Inference from mixed-membership models can produce different output matrices when repeatedly applied to the same inputs, and the number of latent clusters is a parameter that is often varied in the analysis pipeline. For these reasons, quantifying, visualizing, and annotating the output from mixed-membership models are bottlenecks for investigators across multiple disciplines from ecology to text data mining. We introduce pong, a network-graphical approach for analyzing and visualizing membership in latent clusters with a native interactive D3.js visualization. pong leverages efficient algorithms for solving the Assignment Problem to dramatically reduce runtime while increasing accuracy compared with other methods that process output from mixed-membership models. We apply pong to 225 705 unlinked genome-wide single-nucleotide variants from 2426 unrelated individuals in the 1000 Genomes Project, and identify previously overlooked aspects of global human population structure. We show that pong outpaces current solutions by more than an order of magnitude in runtime while providing a customizable and interactive visualization of population structure that is more accurate than those produced by current tools. pong is freely available and can be installed using the Python package management system pip. pong's source code is available at https://github.com/abehr/pong aaron_behr@alumni.brown.edu or sramachandran@brown.edu Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

Do gamblers eat more salt? Testing a latent trait model of covariance in consumption.

PubMed

Goodwin, Belinda C; Browne, Matthew; Rockloff, Matthew; Donaldson, Phillip

2015-09-01

A diverse class of stimuli, including certain foods, substances, media, and economic behaviours, may be described as 'reward-oriented' in that they provide immediate reinforcement with little initial investment. Neurophysiological and personality concepts, including dopaminergic dysfunction, reward sensitivity and rash impulsivity, each predict the existence of a latent behavioural trait that leads to increased consumption of all stimuli in this class. Whilst bivariate relationships (co-morbidities) are often reported in the literature, to our knowledge, a multivariate investigation of this possible trait has not been done. We surveyed 1,194 participants (550 male) on their typical weekly consumption of 11 types of reward-oriented stimuli, including fast food, salt, caffeine, television, gambling products, and illicit drugs. Confirmatory factor analysis was used to compare models in a 3×3 structure, based on the definition of a single latent factor (none, fixed loadings, or estimated loadings), and assumed residual covariance structure (none, a-priori / literature based, or post-hoc / data-driven). The inclusion of a single latent behavioural 'consumption' factor significantly improved model fit in all cases. Also confirming theoretical predictions, estimated factor loadings on reward-oriented indicators were uniformly positive, regardless of assumptions regarding residual covariances. Additionally, the latent trait was found to be negatively correlated with the non-reward-oriented indicators of fruit and vegetable consumption. The findings support the notion of a single behavioural trait leading to increased consumption of reward-oriented stimuli across multiple modalities. We discuss implications regarding the concentration of negative lifestyle-related health behaviours.

PTSD's latent structure in Malaysian tsunami victims: assessing the newly proposed Dysphoric Arousal model.

PubMed

Armour, Cherie; Raudzah Ghazali, Siti; Elklit, Ask

2013-03-30

The underlying latent structure of Posttraumatic Stress Disorder (PTSD) is widely researched. However, despite a plethora of factor analytic studies, no single model has consistently been shown as superior to alternative models. The two most often supported models are the Emotional Numbing and the Dysphoria models. However, a recently proposed five-factor Dysphoric Arousal model has been gathering support over and above existing models. Data for the current study were gathered from Malaysian Tsunami survivors (N=250). Three competing models (Emotional Numbing/Dysphoria/Dysphoric Arousal) were specified and estimated using Confirmatory Factor Analysis (CFA). The Dysphoria model provided superior fit to the data compared to the Emotional Numbing model. However, using chi-square difference tests, the Dysphoric Arousal model showed a superior fit compared to both the Emotional Numbing and Dysphoria models. In conclusion, the current results suggest that the Dysphoric Arousal model better represents PTSD's latent structure and that items measuring sleeping difficulties, irritability/anger and concentration difficulties form a separate, unique PTSD factor. These results are discussed in relation to the role of Hyperarousal in PTSD's on-going symptom maintenance and in relation to the DSM-5. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

"Social Anxiety Disorder Carved at its Joints": evidence for the taxonicity of social anxiety disorder.

PubMed

Weeks, Justin W; Carleton, R Nicholas; Asmundson, Gordon J G; McCabe, Randi E; Antony, Martin M

2010-10-01

Previous findings suggest that social anxiety disorder may be best characterized as having a dimensional latent structure (Kollman et al., 2006; Weeks et al., 2009). We attempted to extend previous taxometric investigations of social anxiety by examining the latent structure of social anxiety disorder symptoms in a large sample comprised of social anxiety disorder patients (i.e., putative taxon members) and community residents/undergraduate respondents (i.e., putative complement class members). MAXEIG and MAMBAC were performed with indicator sets drawn from a self-report measure of social anxiety symptoms, the Social Interaction Phobia Scale (Carleton et al., 2009). MAXEIG and MAMBAC analyses, as well as comparison analyses utilizing simulated taxonic and dimensional datasets, yielded converging evidence that social anxiety disorder has a taxonic latent structure. Moreover, 100% of the confirmed social anxiety disorder patients in our overall sample were correctly assigned to the identified taxon class, providing strong support for the external validity of the identified taxon; and k-means cluster analysis results corroborated our taxometric base-rate estimates. Implications regarding the conceptualization, diagnosis, and assessment of social anxiety disorder are discussed. Copyright 2010 Elsevier Ltd. All rights reserved.

Multilevel structural equation models for assessing moderation within and across levels of analysis.

PubMed

Preacher, Kristopher J; Zhang, Zhen; Zyphur, Michael J

2016-06-01

Social scientists are increasingly interested in multilevel hypotheses, data, and statistical models as well as moderation or interactions among predictors. The result is a focus on hypotheses and tests of multilevel moderation within and across levels of analysis. Unfortunately, existing approaches to multilevel moderation have a variety of shortcomings, including conflated effects across levels of analysis and bias due to using observed cluster averages instead of latent variables (i.e., "random intercepts") to represent higher-level constructs. To overcome these problems and elucidate the nature of multilevel moderation effects, we introduce a multilevel structural equation modeling (MSEM) logic that clarifies the nature of the problems with existing practices and remedies them with latent variable interactions. This remedy uses random coefficients and/or latent moderated structural equations (LMS) for unbiased tests of multilevel moderation. We describe our approach and provide an example using the publicly available High School and Beyond data with Mplus syntax in Appendix. Our MSEM method eliminates problems of conflated multilevel effects and reduces bias in parameter estimates while offering a coherent framework for conceptualizing and testing multilevel moderation effects. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Enhanced Thermal Properties of Novel Latent Heat Thermal Storage Material Through Confinement of Stearic Acid in Meso-Structured Onion-Like Silica

NASA Astrophysics Data System (ADS)

Gao, Junkai; Lv, Mengjiao; Lu, Jinshu; Chen, Yan; Zhang, Zijun; Zhang, Xiongjie; Zhu, Yingying

2017-12-01

Meso-structured onion-like silica (MOS), which had a highly ordered, onion-like multilayer; large surface area and pore volume; and highly curved mesopores, were synthesized as a support for stearic acid (SA) to develop a novel shape-stabilized phase change material (SA/MOS). The characterizations of SA/MOS were studied by the analysis technique of scanning electron microscope, infrared spectroscopy, x-ray diffraction, differential scanning calorimeter (DSC), and thermal gravimetry analysis (TGA). The results showed that the interaction between the SA and the MOS was physical adsorption and that the MOS had no effect on the crystal structure of the SA. The DSC results suggested that the melting and solidifying temperature of the SA/MOS were 72.7°C and 63.9°C with a melting latent heat of 108.0 J/g and a solidifying latent heat of 126.0 J/g, respectively, and the TGA results indicated that the SA/MOS had a good thermal stability. All of the results demonstrated that the SA/MOS was a promising thermal energy storage material candidate for practical applications.

The consequences of ignoring measurement invariance for path coefficients in structural equation models

PubMed Central

Guenole, Nigel; Brown, Anna

2014-01-01

We report a Monte Carlo study examining the effects of two strategies for handling measurement non-invariance – modeling and ignoring non-invariant items – on structural regression coefficients between latent variables measured with item response theory models for categorical indicators. These strategies were examined across four levels and three types of non-invariance – non-invariant loadings, non-invariant thresholds, and combined non-invariance on loadings and thresholds – in simple, partial, mediated and moderated regression models where the non-invariant latent variable occupied predictor, mediator, and criterion positions in the structural regression models. When non-invariance is ignored in the latent predictor, the focal group regression parameters are biased in the opposite direction to the difference in loadings and thresholds relative to the referent group (i.e., lower loadings and thresholds for the focal group lead to overestimated regression parameters). With criterion non-invariance, the focal group regression parameters are biased in the same direction as the difference in loadings and thresholds relative to the referent group. While unacceptable levels of parameter bias were confined to the focal group, bias occurred at considerably lower levels of ignored non-invariance than was previously recognized in referent and focal groups. PMID:25278911

Allergic Asthmatics Show Divergent Lipid Mediator Profiles from Healthy Controls Both at Baseline and following Birch Pollen Provocation

PubMed Central

Lundström, Susanna L.; Yang, Jun; Källberg, Henrik J.; Thunberg, Sarah; Gafvelin, Guro; Haeggström, Jesper Z.; Grönneberg, Reidar; Grunewald, Johan; van Hage, Marianne; Hammock, Bruce D.; Eklund, Anders; Wheelock, Åsa M.; Wheelock, Craig E.

2012-01-01

Background Asthma is a respiratory tract disorder characterized by airway hyper-reactivity and chronic inflammation. Allergic asthma is associated with the production of allergen-specific IgE and expansion of allergen-specific T-cell populations. Progression of allergic inflammation is driven by T-helper type 2 (Th2) mediators and is associated with alterations in the levels of lipid mediators. Objectives Responses of the respiratory system to birch allergen provocation in allergic asthmatics were investigated. Eicosanoids and other oxylipins were quantified in the bronchoalveolar lumen to provide a measure of shifts in lipid mediators associated with allergen challenge in allergic asthmatics. Methods Eighty-seven lipid mediators representing the cyclooxygenase (COX), lipoxygenase (LOX) and cytochrome P450 (CYP) metabolic pathways were screened via LC-MS/MS following off-line extraction of bronchoalveolar lavage fluid (BALF). Multivariate statistics using OPLS were employed to interrogate acquired oxylipin data in combination with immunological markers. Results Thirty-two oxylipins were quantified, with baseline asthmatics possessing a different oxylipin profile relative to healthy individuals that became more distinct following allergen provocation. The most prominent differences included 15-LOX-derived ω-3 and ω-6 oxylipins. Shared-and-Unique-Structures (SUS)-plot modeling showed a correlation (R2 = 0.7) between OPLS models for baseline asthmatics (R2Y[cum] = 0.87, Q2[cum] = 0.51) and allergen-provoked asthmatics (R2Y[cum] = 0.95, Q2[cum] = 0.73), with the majority of quantified lipid mediators and cytokines contributing equally to both groups. Unique structures for allergen provocation included leukotrienes (LTB4 and 6-trans-LTB4), CYP-derivatives of linoleic acid (epoxides/diols), and IL-10. Conclusions Differences in asthmatic relative to healthy profiles suggest a role for 15-LOX products of both ω-6 and ω-3 origin in allergic inflammation. Prominent differences at baseline levels indicate that non-symptomatic asthmatics are subject to an underlying inflammatory condition not observed with other traditional mediators. Results suggest that oxylipin profiling may provide a sensitive means of characterizing low-level inflammation and that even individuals with mild disease display distinct phenotypic profiles, which may have clinical ramifications for disease. PMID:22438998

Multi-Disciplinary Ocean Sensors for Environmental Analyses and Networks (MOSEAN)

DTIC Science & Technology

2004-01-01

will require optimization for their application . Modifications will include: a) Size and power reduction of the electro-fluidic component to match...be configured for detection of CDOM, phycocyanin , phycoerythrin, and chlorophyll-a depending upon the specific wavelengths chosen. Efforts on this...OPL in Santa Barbara. Discussions centered on new instrumentation designed for coastal applications and plans for the CHARM mooring (site selection

Multi-disciplinary Ocean Sensors for Environmental Analyses and Networks (MOSEAN)

DTIC Science & Technology

2003-09-30

will require optimization for their application . Modifications will include: a) Size and power reduction of the electro-fluidic component to match...instrument can be configured for detection of CDOM, phycocyanin , phycoerythrin, and chlorophyll-a depending upon the specific wavelengths chosen. Efforts...OPL in Santa Barbara. Discussions centered on new instrumentation designed for coastal applications and plans for the CHARM mooring (site selection

Comparative analysis of targeted metabolomics: dominance-based rough set approach versus orthogonal partial least square-discriminant analysis.

PubMed

Blasco, H; Błaszczyński, J; Billaut, J C; Nadal-Desbarats, L; Pradat, P F; Devos, D; Moreau, C; Andres, C R; Emond, P; Corcia, P; Słowiński, R

2015-02-01

Metabolomics is an emerging field that includes ascertaining a metabolic profile from a combination of small molecules, and which has health applications. Metabolomic methods are currently applied to discover diagnostic biomarkers and to identify pathophysiological pathways involved in pathology. However, metabolomic data are complex and are usually analyzed by statistical methods. Although the methods have been widely described, most have not been either standardized or validated. Data analysis is the foundation of a robust methodology, so new mathematical methods need to be developed to assess and complement current methods. We therefore applied, for the first time, the dominance-based rough set approach (DRSA) to metabolomics data; we also assessed the complementarity of this method with standard statistical methods. Some attributes were transformed in a way allowing us to discover global and local monotonic relationships between condition and decision attributes. We used previously published metabolomics data (18 variables) for amyotrophic lateral sclerosis (ALS) and non-ALS patients. Principal Component Analysis (PCA) and Orthogonal Partial Least Square-Discriminant Analysis (OPLS-DA) allowed satisfactory discrimination (72.7%) between ALS and non-ALS patients. Some discriminant metabolites were identified: acetate, acetone, pyruvate and glutamine. The concentrations of acetate and pyruvate were also identified by univariate analysis as significantly different between ALS and non-ALS patients. DRSA correctly classified 68.7% of the cases and established rules involving some of the metabolites highlighted by OPLS-DA (acetate and acetone). Some rules identified potential biomarkers not revealed by OPLS-DA (beta-hydroxybutyrate). We also found a large number of common discriminating metabolites after Bayesian confirmation measures, particularly acetate, pyruvate, acetone and ascorbate, consistent with the pathophysiological pathways involved in ALS. DRSA provides a complementary method for improving the predictive performance of the multivariate data analysis usually used in metabolomics. This method could help in the identification of metabolites involved in disease pathogenesis. Interestingly, these different strategies mostly identified the same metabolites as being discriminant. The selection of strong decision rules with high value of Bayesian confirmation provides useful information about relevant condition-decision relationships not otherwise revealed in metabolomics data. Copyright © 2014 Elsevier Inc. All rights reserved.

PDMS based photonic lab-on-a-chip for the selective optical detection of heavy metal ions.

PubMed

Ibarlucea, Bergoi; Díez-Gil, César; Ratera, Inma; Veciana, Jaume; Caballero, Antonio; Zapata, Fabiola; Tárraga, Alberto; Molina, Pedro; Demming, Stephanie; Büttgenbach, Stephanus; Fernández-Sánchez, César; Llobera, Andreu

2013-02-21

The selective absorbance detection of mercury(II) (Hg(2+)) and lead(II) (Pb(2+)) ions using ferrocene-based colorimetric ligands and miniaturized multiple internal reflection (MIR) systems implemented in a low-cost photonic lab on a chip (PhLoC) is reported. The detection principle is based on the formation of selective stable complexes between the heavy metal ion and the corresponding ligand. This interaction modulates the ligand spectrum by giving rise to new absorbance bands or wavelength shifting of the existing ones. A comparative study for the detection of Hg(2+) was carried out with two MIR-based PhLoC systems showing optical path lengths (OPLs) of 0.64 cm and 1.42 cm as well as a standard cuvette (1.00 cm OPL). Acetonitrile solutions containing the corresponding ligand and increasing concentrations of the heavy metal ion were pumped inside the systems and the absorbance in the visible region of the spectra was recorded. The optical behaviour of all the tested systems followed the expected Beer-Lambert law. Thus, the best results were achieved with the one with the longest OPL, which showed a linear behaviour in a concentration range of 1 μM-90 μM Hg(2+), a sensitivity of 5.6 × 10(-3) A.U. μM(-1) and a LOD of 2.59 μM (0.49 ppm), this being 1.7 times lower than that recorded with a standard cuvette, and using a sample/reagent volume around 190 times smaller. This microsystem was also applied for the detection of Pb(2+) and a linear behaviour in a concentration range of 3-100 μM was obtained, and a sensitivity of 9.59 × 10(-4) A.U. μM(-1) and a LOD of 4.19 μM (0.868 ppm) were achieved. Such a simple analytical tool could be implemented in portable instruments for automatic in-field measurements and, considering the minute sample and reagent volume required, would enable the deployment of high throughput environmental analysis of these pollutants and other related hazardous species.

Psychometric Structure of a Comprehensive Objective Structured Clinical Examination: A Factor Analytic Approach

ERIC Educational Resources Information Center

Volkan, Kevin; Simon, Steven R.; Baker, Harley; Todres, I. David

2004-01-01

Problem Statement and Background: While the psychometric properties of Objective Structured Clinical Examinations (OSCEs) have been studied, their latent structures have not been well characterized. This study examines a factor analytic model of a comprehensive OSCE and addresses implications for measurement of clinical performance. Methods: An…

RADC (Rome Air Development Center) Guide to Environmental Stress Screening

DTIC Science & Technology

1986-08-01

and the processes which are used in their manufacture. ESS is the vehicle by which latent defects are accelerated to early failure in the factory. ESS...structured as part of a production 2 reliability assurance program, is the vehicle through which product reliability in manufacture can be maintained...mechanical, electrical and/or thermal stresses to an equipment item for the purpose of precipitating latent part and workmanship defects to early failure

A new model of wheezing severity in young children using the validated ISAAC wheezing module: A latent variable approach with validation in independent cohorts.

PubMed

Brunwasser, Steven M; Gebretsadik, Tebeb; Gold, Diane R; Turi, Kedir N; Stone, Cosby A; Datta, Soma; Gern, James E; Hartert, Tina V

2018-01-01

The International Study of Asthma and Allergies in Children (ISAAC) Wheezing Module is commonly used to characterize pediatric asthma in epidemiological studies, including nearly all airway cohorts participating in the Environmental Influences on Child Health Outcomes (ECHO) consortium. However, there is no consensus model for operationalizing wheezing severity with this instrument in explanatory research studies. Severity is typically measured using coarsely-defined categorical variables, reducing power and potentially underestimating etiological associations. More precise measurement approaches could improve testing of etiological theories of wheezing illness. We evaluated a continuous latent variable model of pediatric wheezing severity based on four ISAAC Wheezing Module items. Analyses included subgroups of children from three independent cohorts whose parents reported past wheezing: infants ages 0-2 in the INSPIRE birth cohort study (Cohort 1; n = 657), 6-7-year-old North American children from Phase One of the ISAAC study (Cohort 2; n = 2,765), and 5-6-year-old children in the EHAAS birth cohort study (Cohort 3; n = 102). Models were estimated using structural equation modeling. In all cohorts, covariance patterns implied by the latent variable model were consistent with the observed data, as indicated by non-significant χ2 goodness of fit tests (no evidence of model misspecification). Cohort 1 analyses showed that the latent factor structure was stable across time points and child sexes. In both cohorts 1 and 3, the latent wheezing severity variable was prospectively associated with wheeze-related clinical outcomes, including physician asthma diagnosis, acute corticosteroid use, and wheeze-related outpatient medical visits when adjusting for confounders. We developed an easily applicable continuous latent variable model of pediatric wheezing severity based on items from the well-validated ISAAC Wheezing Module. This model prospectively associates with asthma morbidity, as demonstrated in two ECHO birth cohort studies, and provides a more statistically powerful method of testing etiologic hypotheses of childhood wheezing illness and asthma.

Toxicity and Detoxification Effects of Herbal Caowu via Ultra Performance Liquid Chromatography/Mass Spectrometry Metabolomics Analyzed using Pattern Recognition Method

PubMed Central

Yan, Yan; Zhang, Aihua; Dong, Hui; Yan, Guangli; Sun, Hui; Wu, Xiuhong; Han, Ying; Wang, Xijun

2017-01-01

Background: Caowu (Radix Aconiti kusnezoffii, CW), the root of Aconitum kusnezoffii Reichb., has widely used clinically in rheumatic arthritis, painful joints, and tumors for thousands of years. However, the toxicity of heart and central nervous system induced by CW still limited the application. Materials and Methods: Metabolomics was performed to identify the sensitive and reliable biomarkers and to characterize the phenotypically biochemical perturbations and potential mechanisms of CW-induced toxicity, and the detoxification by combinatorial intervention of CW with Gancao (Radix Glycyrrhizae) (CG), Baishao (Radix Paeoniae Alba) (CB), and Renshen (Radix Ginseng) (CR) was also analyzed by pattern recognition methods. Results: As a result, the metabolites were characterized and responsible for pentose and glucuronate interconversions, tryptophan metabolism, amino sugar and nucleotide sugar metabolism, taurine and hypotaurine metabolism, fructose and mannose metabolism, and starch and sucrose metabolism, six networks of which were the same to the metabolic pathways of Chuanwu (Radix Aconiti, CHW) group. The ascorbate and aldarate metabolism was also characterized by CW group. The urinary metabolomics also revealed CW-induced serious toxicity to heart and liver. Thirteen significant metabolites were identified and had validated as phenotypic toxicity biomarkers of CW, five biomarkers of which were commonly owned in Aconitum. The changes of toxicity metabolites obtained from combinatorial intervention of CG, CB, and CR also were analyzed to investigate the regulation degree of toxicity biomarkers adjusted by different combinatorial interventions at 6th month. Conclusion: Metabolomics analyses coupled with pattern recognition methods in the evaluation of drug toxicity and finding detoxification methods were highlighted in this work. SUMMARY Metabolomics was performed to characterize the biochemical potential mechanisms of Caowu toxicityThirteen significant metabolites were identified and validated as phenotypic toxicity biomarkers of CaowuMetabolite changes of toxicity obtained can be adjusted by different combinatorial interventions.Pattern recognition plot reflects the toxicity effects tendency of the urine metabolic fluctuations according to time after treatment of herbal Caowu. Abbreviations used: CW: Caowu (Radix Aconiti kusnezoffii); CHW: Chuanwu (Radix Aconiti); TCM: Traditional Chinese Medicine; CG: Caowu and Gancao; CB: Caowu and Baishao; CR: Caowu and Renshen; QC: Quality control; UPLC: Ultra performance liquid chromatography; MS: Mass spectrometry; PCA: Principal component analysis; PLS-DA: Partial least squares-discriminant analysis; OPLS: Orthogonal projection to latent structures analysis. PMID:29200734

Quantitative proteomics reveals protein profiles underlying major transitions in aspen wood development.

PubMed

Obudulu, Ogonna; Bygdell, Joakim; Sundberg, Björn; Moritz, Thomas; Hvidsten, Torgeir R; Trygg, Johan; Wingsle, Gunnar

2016-02-18

Wood development is of outstanding interest both to basic research and industry due to the associated cellulose and lignin biomass production. Efforts to elucidate wood formation (which is essential for numerous aspects of both pure and applied plant science) have been made using transcriptomic analyses and/or low-resolution sampling. However, transcriptomic data do not correlate perfectly with levels of expressed proteins due to effects of post-translational modifications and variations in turnover rates. In addition, high-resolution analysis is needed to characterize key transitions. In order to identify protein profiles across the developmental region of wood formation, an in-depth and tissue specific sampling was performed. We examined protein profiles, using an ultra-performance liquid chromatography/quadrupole time of flight mass spectrometry system, in high-resolution tangential sections spanning all wood development zones in Populus tremula from undifferentiated cambium to mature phloem and xylem, including cell expansion and cell death zones. In total, we analyzed 482 sections, 20-160 μm thick, from four 47-year-old trees growing wild in Sweden. We obtained high quality expression profiles for 3,082 proteins exhibiting consistency across the replicates, considering that the trees were growing in an uncontrolled environment. A combination of Principal Component Analysis (PCA), Orthogonal Projections to Latent Structures (OPLS) modeling and an enhanced stepwise linear modeling approach identified several major transitions in global protein expression profiles, pinpointing (for example) locations of the cambial division leading to phloem and xylem cells, and secondary cell wall formation zones. We also identified key proteins and associated pathways underlying these developmental landmarks. For example, many of the lignocellulosic related proteins were upregulated in the expansion to the early developmental xylem zone, and for laccases with a rapid decrease in early xylem zones. We observed upregulation of two forms of xylem cysteine protease (Potri.002G005700.1 and Potri.005G256000.2; Pt-XCP2.1) in early xylem and their downregulation in late maturing xylem. Our data also show that Pt-KOR1.3 (Potri.003G151700.2) exhibits an expression pattern that supports the hypothesis put forward in previous studies that this is a key xyloglucanase involved in cellulose biosynthesis in primary cell walls and reduction of cellulose crystallinity in secondary walls. Our novel multivariate approach highlights important processes and provides confirmatory insights into the molecular foundations of wood development.

Structure of Alzheimer's 10-35 β peptide from replica-exchange molecular dynamics simulations in explicit water

NASA Astrophysics Data System (ADS)

Baumketner, Andriy; Shea, Joan-Emma

2006-03-01

We report a replica-exchange molecular dynamics study of the 10-35 fragment of Alzheimer's disease amyloid β peptide, Aβ10-35, in aqueous solution. This fragment was previously seen [J. Str. Biol. 130 (2000) 130] to possess all the most important amyloidogenic properties characteristic of full-length Aβ peptides. Our simulations attempted to fold Aβ10-35 from first principles. The peptide was modeled using all-atom OPLS/AA force field in conjunction with the TIP3P explicit solvent model. A total of 72 replicas were considered and simulated over 40 ns of total time, including 5 ns of initial equilibration. We find that Aβ10-35 does not possess any unique folded state, a 3D structure of predominant population, under normal temperature and pressure. Rather, this peptide exists as a mixture of collapsed globular states that remain in rapid dynamic equilibrium with each other. This conformational ensemble is seen to be dominated by random coil and bend structures with insignificant presence of α-helical or β-sheet structure. We find that, overall, the 3D structure of Aβ10-35 is shaped by salt bridges formed between oppositely charged residues.Of all possible salt bridges, K28-D23 was seen to have the highest formation probability, totaling more than 60% of the time.

Social phobia: further evidence of dimensional structure.

PubMed

Crome, Erica; Baillie, Andrew; Slade, Tim; Ruscio, Ayelet Meron

2010-11-01

Social phobia is a common mental disorder associated with significant impairment. Current research and treatment models of social phobia rely on categorical diagnostic conceptualizations lacking empirical support. This study aims to further research exploring whether social phobia is best conceptualized as a dimension or a discrete categorical disorder. This study used three distinct taxometric techniques (mean above minus below a cut, maximum Eigen value and latent mode) to explore the latent structure of social phobia in two large epidemiological samples, using indicators derived from diagnostic criteria and associated avoidant personality traits. Overall, outcomes from multiple taxometric analyses supported dimensional structure. This is consistent with conceptualizations of social phobia as lying on a continuum with avoidant personality traits. Support for the dimensionality of social phobia has important implications for future research, assessment, treatment, and public policy.

Reconceptualizing the classification of PNAS articles

PubMed Central

Airoldi, Edoardo M.; Erosheva, Elena A.; Fienberg, Stephen E.; Joutard, Cyrille; Love, Tanzy; Shringarpure, Suyash

2010-01-01

PNAS article classification is rooted in long-standing disciplinary divisions that do not necessarily reflect the structure of modern scientific research. We reevaluate that structure using latent pattern models from statistical machine learning, also known as mixed-membership models, that identify semantic structure in co-occurrence of words in the abstracts and references. Our findings suggest that the latent dimensionality of patterns underlying PNAS research articles in the Biological Sciences is only slightly larger than the number of categories currently in use, but it differs substantially in the content of the categories. Further, the number of articles that are listed under multiple categories is only a small fraction of what it should be. These findings together with the sensitivity analyses suggest ways to reconceptualize the organization of papers published in PNAS. PMID:21078953

Labour management and Obstetric outcomes among pregnant women admitted in latent phase compared to active phase of labour at Bugando Medical Centre in Tanzania

PubMed Central

2014-01-01

Background Interventions given to women admitted in latent or active phase of labor may influence the outcomes of labor and ameliorate complications which can affect the mother and fetus. Labour management, maternal and fetal outcomes among low risk women presenting both in latent phase and active phase of labour in Tanzania have not recently been explored. Methods This was a descriptive cross-sectional study. It was done from February to April 2013. Case notes were collected serially until the sample size was reached. A structured checklist was used to extract data. Data was analyzed using SPSS version 17. A p < 0.05 was considered significant at 95% confidence interval. Results Five hundred case notes of low risk pregnant women were collected, half of each presented in latent phase and active phase of labour. Key interventions including augmentation with oxytocin, artificial rupture of membranes and caesarean section were significantly higher in the latent phase group than the active phase group 84(33.6%) versus 52(20.8%) p < 0.05; 96(38.6%) versus 56(22.4%) p < 0.05 and 87(34.8%) versus 60(24.0%) p < 0.05 respectively. Spontaneous vertex delivery was higher among pregnant women admitted initially in active phase than in latent phase groups 180(72.0%), versus 153(61.2%) p > 0.01). There were more women in the active phase group who sustained genital tract tear and postpartum haemorrhage than in the latent phase group 101(18.6%), versus 38(15.6%) p < 0.01 and 46(18.4%), versus 17(6.6%) p < 0.05 respectively. Conclusions Pregnant women admitted at BMC in latent phase of labour are subjected to more obstetric interventions than those admitted in the active phase. There is need to produce guidelines on management of women admitted in latent phase of labour at BMC to reduce the risk of unnecessary interventions. PMID:24521301

Labour management and Obstetric outcomes among pregnant women admitted in latent phase compared to active phase of labour at Bugando Medical Centre in Tanzania.

PubMed

Chuma, Clotrida; Kihunrwa, Albert; Matovelo, Dismas; Mahendeka, Marietha

2014-02-12

Interventions given to women admitted in latent or active phase of labor may influence the outcomes of labor and ameliorate complications which can affect the mother and fetus. Labour management, maternal and fetal outcomes among low risk women presenting both in latent phase and active phase of labour in Tanzania have not recently been explored. This was a descriptive cross-sectional study. It was done from February to April 2013. Case notes were collected serially until the sample size was reached. A structured checklist was used to extract data. Data was analyzed using SPSS version 17. A p < 0.05 was considered significant at 95% confidence interval. Five hundred case notes of low risk pregnant women were collected, half of each presented in latent phase and active phase of labour. Key interventions including augmentation with oxytocin, artificial rupture of membranes and caesarean section were significantly higher in the latent phase group than the active phase group 84(33.6%) versus 52(20.8%) p < 0.05; 96(38.6%) versus 56(22.4%) p < 0.05 and 87(34.8%) versus 60(24.0%) p < 0.05 respectively. Spontaneous vertex delivery was higher among pregnant women admitted initially in active phase than in latent phase groups 180(72.0%), versus 153(61.2%) p > 0.01). There were more women in the active phase group who sustained genital tract tear and postpartum haemorrhage than in the latent phase group 101(18.6%), versus 38(15.6%) p < 0.01 and 46(18.4%), versus 17(6.6%) p < 0.05 respectively. Pregnant women admitted at BMC in latent phase of labour are subjected to more obstetric interventions than those admitted in the active phase. There is need to produce guidelines on management of women admitted in latent phase of labour at BMC to reduce the risk of unnecessary interventions.

Do recognizable lifetime eating disorder phenotypes naturally occur in a culturally asian population? A combined latent profile and taxometric approach.

PubMed

Thomas, Jennifer J; Eddy, Kamryn T; Ruscio, John; Ng, King Lam; Casale, Kristen E; Becker, Anne E; Lee, Sing

2015-05-01

We examined whether empirically derived eating disorder (ED) categories in Hong Kong Chinese patients (N = 454) would be consistent with recognizable lifetime ED phenotypes derived from latent structure models of European and American samples. We performed latent profile analysis (LPA) using indicator variables from data collected during routine assessment, and then applied taxometric analysis to determine whether latent classes were qualitatively versus quantitatively distinct. Latent profile analysis identified four classes: (i) binge/purge (47%); (ii) non-fat-phobic low-weight (34%); (iii) fat-phobic low-weight (12%); and (iv) overweight disordered eating (6%). Taxometric analysis identified qualitative (categorical) distinctions between the binge/purge and non-fat-phobic low-weight classes, and also between the fat-phobic and non-fat-phobic low-weight classes. Distinctions between the fat-phobic low-weight and binge/purge classes were indeterminate. Empirically derived categories in Hong Kong showed recognizable correspondence with recognizable lifetime ED phenotypes. Although taxometric findings support two distinct classes of low weight EDs, LPA findings also support heterogeneity among non-fat-phobic individuals. Copyright © 2015 John Wiley & Sons, Ltd and Eating Disorders Association.

Dictionary Pruning with Visual Word Significance for Medical Image Retrieval

PubMed Central

Zhang, Fan; Song, Yang; Cai, Weidong; Hauptmann, Alexander G.; Liu, Sidong; Pujol, Sonia; Kikinis, Ron; Fulham, Michael J; Feng, David Dagan; Chen, Mei

2016-01-01

Content-based medical image retrieval (CBMIR) is an active research area for disease diagnosis and treatment but it can be problematic given the small visual variations between anatomical structures. We propose a retrieval method based on a bag-of-visual-words (BoVW) to identify discriminative characteristics between different medical images with Pruned Dictionary based on Latent Semantic Topic description. We refer to this as the PD-LST retrieval. Our method has two main components. First, we calculate a topic-word significance value for each visual word given a certain latent topic to evaluate how the word is connected to this latent topic. The latent topics are learnt, based on the relationship between the images and words, and are employed to bridge the gap between low-level visual features and high-level semantics. These latent topics describe the images and words semantically and can thus facilitate more meaningful comparisons between the words. Second, we compute an overall-word significance value to evaluate the significance of a visual word within the entire dictionary. We designed an iterative ranking method to measure overall-word significance by considering the relationship between all latent topics and words. The words with higher values are considered meaningful with more significant discriminative power in differentiating medical images. We evaluated our method on two public medical imaging datasets and it showed improved retrieval accuracy and efficiency. PMID:27688597

Dictionary Pruning with Visual Word Significance for Medical Image Retrieval.

PubMed

Zhang, Fan; Song, Yang; Cai, Weidong; Hauptmann, Alexander G; Liu, Sidong; Pujol, Sonia; Kikinis, Ron; Fulham, Michael J; Feng, David Dagan; Chen, Mei

2016-02-12

Content-based medical image retrieval (CBMIR) is an active research area for disease diagnosis and treatment but it can be problematic given the small visual variations between anatomical structures. We propose a retrieval method based on a bag-of-visual-words (BoVW) to identify discriminative characteristics between different medical images with Pruned Dictionary based on Latent Semantic Topic description. We refer to this as the PD-LST retrieval. Our method has two main components. First, we calculate a topic-word significance value for each visual word given a certain latent topic to evaluate how the word is connected to this latent topic. The latent topics are learnt, based on the relationship between the images and words, and are employed to bridge the gap between low-level visual features and high-level semantics. These latent topics describe the images and words semantically and can thus facilitate more meaningful comparisons between the words. Second, we compute an overall-word significance value to evaluate the significance of a visual word within the entire dictionary. We designed an iterative ranking method to measure overall-word significance by considering the relationship between all latent topics and words. The words with higher values are considered meaningful with more significant discriminative power in differentiating medical images. We evaluated our method on two public medical imaging datasets and it showed improved retrieval accuracy and efficiency.

Striking the right immunological balance prevents progression of tuberculosis.

PubMed

Vyas, Shachi Pranjal; Goswami, Ritobrata

2017-12-01

Tuberculosis (TB) caused by infection with Mycobacterium tuberculosis (Mtb) is a major burden for human health worldwide. Current standard treatments for TB require prolonged administration of antimycobacterial drugs leading to exaggerated inflammation and tissue damage. This can result in the reactivation of latent TB culminating in TB progression. Thus, there is an unmet need to develop therapies that would shorten the duration of anti-TB treatment and to induce optimal protective immune responses to control the spread of mycobacterial infection with minimal lung pathology. Granulomata is the hallmark structure formed by the organized accumulation of immune cells including macrophages, natural killer cells, dendritic cells, neutrophils, T cells, and B cells to the site of Mtb infection. It safeguards the host by containing Mtb in latent form. However, granulomata can undergo caseation and contribute to the reactivation of latent TB, if the immune responses developed to fight mycobacterial infection are not properly controlled. Thus, an optimal balance between innate and adaptive immune cells might play a vital role in containing mycobacteria in latent form for prolonged periods and prevent the spread of Mtb infection from one individual to another. Optimal and well-regulated immune responses against Mycobacterium tuberculosis may help to prevent the reactivation of latent TB. Moreover, therapies targeting balanced immune responses could help to improve treatment outcomes among latently infected TB patients and thereby limit the dissemination of mycobacterial infection.

Kinetics of Electrons from Plasma Discharge in a Latent Track Region Induced by Swift Heavy ION Irradiation

NASA Astrophysics Data System (ADS)

Minárik, Stanislav

2015-08-01

While passing swift heavy ion through a material structure, it produces a region of radiation affected material which is known as a "latent track". Scattering motions of electrons interacting with a swift heavy ion are dominant in the latent track region. These phenomena include the electron impurity and phonon scattering processes modified by the interaction with the ion projectile as well as the Coulomb scattering between two electrons. In this paper, we provide detailed derivation of a 3D Boltzmann scattering equation for the description of the relative scattering motion of such electrons. Phase-space distribution function for this non-equilibrioum system of scattering electrons can be found by the solution of mentioned equation.

Postnatal functional inactivation of the entorhinal cortex or ventral subiculum has different consequences for latent inhibition-related striatal dopaminergic responses in adult rats.

PubMed

Meyer, F; Peterschmitt, Y; Louilot, A

2009-05-01

Latent inhibition has been found to be disrupted in patients with acute schizophrenia. Striatal dopaminergic dysregulation is commonly acknowledged in schizophrenia. This disease may be consecutive to a functional disconnection between integrative regions, stemming from neurodevelopmental failures. Various anomalies suggesting early abnormal brain development have been described in the entorhinal cortex (ENT) and ventral subiculum (SUB) of patients. This study examines the consequences of a neonatal transitory blockade of the left ENT or left SUB for latent inhibition-related dopamine responses in the anterior part of the dorsal striatum using in-vivo voltammetry in freely moving adult rats. Reversible inactivation of both structures in different animals was achieved by local microinjection of tetrodotoxin (TTX) at postnatal day 8. Results obtained during the retention session of a three-stage latent inhibition protocol showed that the functional neonatal disconnection of the ENT or SUB caused the behavioural latent inhibition expression in pre-exposed (PE)-TTX-conditioned adult rats to disappear. After postnatal inactivation of the SUB, PE-TTX-conditioned rats displayed a reversal of the latent inhibition-related striatal dopamine responses, whereas after neonatal blockade of the ENT, dopamine changes in PE-TTX-conditioned rats monitored in the anterior striatum were between those observed in PE-phosphate-buffered-saline-conditioned and non-PE-TTX-conditioned animals. These data suggest that neonatal functional inactivation of the SUB disrupts latent inhibition-related striatal dopamine responses in adult animals more than that of the ENT. They may help improve understanding of the pathophysiology of schizophrenia.

Recombination enhances HIV-1 envelope diversity by facilitating the survival of latent genomic fragments in the plasma virus population

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

Immonen, Taina T.; Conway, Jessica M.; Romero-Severson, Ethan O.

HIV-1 is subject to immune pressure exerted by the host, giving variants that escape the immune response an advantage. Virus released from activated latent cells competes against variants that have continually evolved and adapted to host immune pressure. Nevertheless, there is increasing evidence that virus displaying a signal of latency survives in patient plasma despite having reduced fitness due to long-term immune memory. We investigated the survival of virus with latent envelope genomic fragments by simulating within-host HIV-1 sequence evolution and the cycling of viral lineages in and out of the latent reservoir. Our model incorporates a detailed mutation processmore » including nucleotide substitution, recombination, latent reservoir dynamics, diversifying selection pressure driven by the immune response, and purifying selection pressure asserted by deleterious mutations. We evaluated the ability of our model to capture sequence evolution in vivo by comparing our simulated sequences to HIV-1 envelope sequence data from 16 HIV-infected untreated patients. Empirical sequence divergence and diversity measures were qualitatively and quantitatively similar to those of our simulated HIV-1 populations, suggesting that our model invokes realistic trends of HIV-1 genetic evolution. Moreover, reconstructed phylogenies of simulated and patient HIV-1 populations showed similar topological structures. Our simulation results suggest that recombination is a key mechanism facilitating the persistence of virus with latent envelope genomic fragments in the productively infected cell population. Recombination increased the survival probability of latent virus forms approximately 13-fold. Prevalence of virus with latent fragments in productively infected cells was observed in only 2% of simulations when we ignored recombination, while the proportion increased to 27% of simulations when we allowed recombination. We also found that the selection pressures exerted by different fitness landscapes influenced the shape of phylogenies, diversity trends, and survival of virus with latent genomic fragments. Furthermore, our model predicts that the persistence of latent genomic fragments from multiple different ancestral origins increases sequence diversity in plasma for reasonable fitness landscapes.« less

Recombination enhances HIV-1 envelope diversity by facilitating the survival of latent genomic fragments in the plasma virus population

DOE PAGES

Immonen, Taina T.; Conway, Jessica M.; Romero-Severson, Ethan O.; ...

2015-12-22

HIV-1 is subject to immune pressure exerted by the host, giving variants that escape the immune response an advantage. Virus released from activated latent cells competes against variants that have continually evolved and adapted to host immune pressure. Nevertheless, there is increasing evidence that virus displaying a signal of latency survives in patient plasma despite having reduced fitness due to long-term immune memory. We investigated the survival of virus with latent envelope genomic fragments by simulating within-host HIV-1 sequence evolution and the cycling of viral lineages in and out of the latent reservoir. Our model incorporates a detailed mutation processmore » including nucleotide substitution, recombination, latent reservoir dynamics, diversifying selection pressure driven by the immune response, and purifying selection pressure asserted by deleterious mutations. We evaluated the ability of our model to capture sequence evolution in vivo by comparing our simulated sequences to HIV-1 envelope sequence data from 16 HIV-infected untreated patients. Empirical sequence divergence and diversity measures were qualitatively and quantitatively similar to those of our simulated HIV-1 populations, suggesting that our model invokes realistic trends of HIV-1 genetic evolution. Moreover, reconstructed phylogenies of simulated and patient HIV-1 populations showed similar topological structures. Our simulation results suggest that recombination is a key mechanism facilitating the persistence of virus with latent envelope genomic fragments in the productively infected cell population. Recombination increased the survival probability of latent virus forms approximately 13-fold. Prevalence of virus with latent fragments in productively infected cells was observed in only 2% of simulations when we ignored recombination, while the proportion increased to 27% of simulations when we allowed recombination. We also found that the selection pressures exerted by different fitness landscapes influenced the shape of phylogenies, diversity trends, and survival of virus with latent genomic fragments. Furthermore, our model predicts that the persistence of latent genomic fragments from multiple different ancestral origins increases sequence diversity in plasma for reasonable fitness landscapes.« less

Targeting NF-κB signaling with protein kinase C agonists as an emerging strategy for combating HIV latency.

PubMed

Jiang, Guochun; Dandekar, Satya

2015-01-01

Highly active antiretroviral therapy (HAART) is very effective in suppressing HIV-1 replication and restoring immune functions in HIV-infected individuals. However, it fails to eradicate the latent viral reservoirs and fully resolve chronic inflammation in HIV infection. The "shock-and-kill" strategy was recently proposed to induce latent HIV expression in the presence of HAART. Recent studies have shown that the protein kinase C (PKC) agonists are highly potent in inducing latent HIV expression from the viral reservoirs in vitro and ex vivo and in protecting primary CD4(+) T cells from HIV infection through down-modulation of their HIV coreceptor expression. The PKC agonists are excellent candidates for advancing to clinical HIV eradication strategies. This article will present a critical review of the structure and function of known PKC agonists, their mechanisms for the reactivation of latent HIV expression, and the potential of these compounds for advancing clinical HIV eradication strategies.

Obtaining systematic teacher reports of disruptive behavior disorders utilizing DSM-IV.

PubMed

Wolraich, M L; Feurer, I D; Hannah, J N; Baumgaertel, A; Pinnock, T Y

1998-04-01

This study examines the psychometric properties of the Vanderbilt AD/HD Diagnostic Teacher Rating Scale (VADTRS) and provides preliminary normative data from a large, geographically defined population. The VADTRS consists of the complete list of DSM-IV AD/HD symptoms, a screen for other disruptive behavior disorders, anxiety and depression, and ratings of academic and classroom behavior performance. Teachers in one suburban county completed the scale for their students during 2 consecutive years. Statistical methods included (a) exploratory and confirmatory latent variable analyses of item data, (b) evaluation of the internal consistency of the latent dimensions, (c) evaluation of latent structure concordance between school year samples, and (d) preliminary evaluation of criterion-related validity. The instrument comprises four behavioral dimensions and two performance dimensions. The behavioral dimensions were concordant between school years and were consistent with a priori DSM-IV diagnostic criteria. Correlations between latent dimensions and relevant, known disorders or problems varied from .25 to .66.

Latent heat contribution to the direct magnetocaloric effect in Ni-Mn-Ga shape memory alloys with coupled martensitic and magnetic transformations

NASA Astrophysics Data System (ADS)

Caballero-Flores, R.; Sánchez-Alarcos, V.; Recarte, V.; Pérez-Landazábal, J. I.; Gómez-Polo, C.

2016-05-01

We report the direct magnetocaloric response of materials that present a second-order phase transition in the temperature range where a first-order structural transition also occurs. In particular, the influence of the latent heat on the field-induced adiabatic temperature change has been analyzed in a Ni-Mn-Ga alloy with coupled martensitic and magnetic transformations. It is found that discrepancies around 20% arise depending on whether the latent heat is taken into account or not. From the observed results, a general expression for the indirect determination of the adiabatic temperature change, that takes into account the contributions of both the martensitic and magnetic transformations, is proposed and experimentally confirmed. The observed key role of the latent heat allows us to understand why materials with first-order transformations do not present adiabatic temperature changes as higher as those which would correspond to materials undergoing second-order transformations with similar isothermal entropy change.

Disgust proneness predicts obsessive-compulsive disorder symptom severity in a clinical sample of youth: Distinctions from negative affect.

PubMed

Olatunji, Bunmi O; Ebesutani, Chad; Kim, Jingu; Riemann, Bradley C; Jacobi, David M

2017-04-15

Although studies have linked disgust proneness to the etiology and maintenance of obsessive-compulsive disorder (OCD) in adults, there remains a paucity of research examining the specificity of this association among youth. The present study employed structural equation modeling to examine the association between disgust proneness, negative affect, and OCD symptom severity in a clinical sample of youth admitted to a residential treatment facility (N =471). Results indicate that disgust proneness and negative affect latent factors independently predicted an OCD symptom severity latent factor. However, when both variables were modeled as predictors simultaneously, latent disgust proneness remained significantly associated with OCD symptom severity, whereas the association between latent negative affect and OCD symptom severity became nonsignificant. Tests of mediation converged in support of disgust proneness as a significant intervening variable between negative affect and OCD symptom severity. Subsequent analysis showed that the path from disgust proneness to OCD symptom severity in the structural model was significantly stronger among those without a primary diagnosis of OCD compared to those with a primary diagnosis of OCD. Given the cross-sectional design, the causal inferences that can be made are limited. The present study is also limited by the exclusive reliance on self-report measures. Disgust proneness may play a uniquely important role in OCD among youth. Copyright © 2017 Elsevier B.V. All rights reserved.

The use of fault reporting of medical equipment to identify latent design flaws.

PubMed

Flewwelling, C J; Easty, A C; Vicente, K J; Cafazzo, J A

2014-10-01

Poor device design that fails to adequately account for user needs, cognition, and behavior is often responsible for use errors resulting in adverse events. This poor device design is also often latent, and could be responsible for "No Fault Found" (NFF) reporting, in which medical devices sent for repair by clinical users are found to be operating as intended. Unresolved NFF reports may contribute to incident under reporting, clinical user frustration, and biomedical engineering technologist inefficacy. This study uses human factors engineering methods to investigate the relationship between NFF reporting frequency and device usability. An analysis of medical equipment maintenance data was conducted to identify devices with a high NFF reporting frequency. Subsequently, semi-structured interviews and heuristic evaluations were performed in order to identify potential usability issues. Finally, usability testing was conducted in order to validate that latent usability related design faults result in a higher frequency of NFF reporting. The analysis of medical equipment maintenance data identified six devices with a high NFF reporting frequency. Semi-structured interviews, heuristic evaluations and usability testing revealed that usability issues caused a significant portion of the NFF reports. Other factors suspected to contribute to increased NFF reporting include accessory issues, intermittent faults and environmental issues. Usability testing conducted on three of the devices revealed 23 latent usability related design faults. These findings demonstrate that latent usability related design faults manifest themselves as an increase in NFF reporting and that devices containing usability related design faults can be identified through an analysis of medical equipment maintenance data. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

Latent Constructs in Psychosocial Factors Associated with Cardiovascular Disease: An Examination by Race and Sex

PubMed Central

Clark, Cari Jo; Henderson, Kimberly M.; de Leon, Carlos F. Mendes; Guo, Hongfei; Lunos, Scott; Evans, Denis A.; Everson-Rose, Susan A.

2012-01-01

This study examines race and sex differences in the latent structure of 10 psychosocial measures and the association of identified factors with self-reported history of coronary heart disease (CHD). Participants were 4,128 older adults from the Chicago Health and Aging Project. Exploratory factor analysis (EFA) with oblique geomin rotation was used to identify latent factors among the psychosocial measures. Multi-group comparisons of the EFA model were conducted using exploratory structural equation modeling to test for measurement invariance across race and sex subgroups. A factor-based scale score was created for invariant factor(s). Logistic regression was used to test the relationship between the factor score(s) and CHD adjusting for relevant confounders. Effect modification of the relationship by race–sex subgroup was tested. A two-factor model fit the data well (comparative fit index = 0.986; Tucker–Lewis index = 0.969; root mean square error of approximation = 0.039). Depressive symptoms, neuroticism, perceived stress, and low life satisfaction loaded on Factor I. Social engagement, spirituality, social networks, and extraversion loaded on Factor II. Only Factor I, re-named distress, showed measurement invariance across subgroups. Distress was associated with a 37% increased odds of self-reported CHD (odds ratio: 1.37; 95% confidence intervals: 1.25, 1.50; p-value < 0.0001). This effect did not differ by race or sex (interaction p-value = 0.43). This study identified two underlying latent constructs among a large range of psychosocial variables; only one, distress, was validly measured across race–sex subgroups. This construct was robustly related to prevalent CHD, highlighting the potential importance of latent constructs as predictors of cardiovascular disease. PMID:22347196

Materials Research Society (MRS) 2014 Fall Meeting, Boston, MA on November 30 December 5, 2014

DTIC Science & Technology

2015-12-18

10.1557/opl.2015.216, Published online by Cambridge University Press 03 Mar 2015 Lithium - ion Diffusion in Solid Electrolyte Interface (SEI) Predicted by...challenges; Innovation and Inclusion: What It Takes to Move Diversity Forward, Vern Myers, Esq., principal of Vern Myers Consulting Group, LLC, engaged...bacteriophage to synthesize radically novel electronic and battery devices at protein and semiconductor interfaces. Ashutosh Chilkoti (Duke Univ

[Evaluation of Brodifacoum-induced Toxicity by Metabonomics Approach Based on HPLC-TOF-MS].

PubMed

Yan, H; Zhuo, X Y; Shen, B H; Xiang, P; Shen, M

2017-06-01

To analyse the metabolic changes in urine of rats with brodifacoum intoxication, and to reveal the molecular mechanism of brodifacoum-induced toxicity on rats. By establishing a brodifacoum poisoning rats model, the urine metabolic profiling data of rats were acquired using high performance liquid chromatography-time of flight mass spectrometry （HPLC-TOF-MS）. The orthogonal partial least squares analysis-discrimination analysis （OPLS-DA） was applied for the multivariate statistics and the discovery of differential metabolites closely related to toxicity of brodifacoum. OPLS-DA score plot showed that the urinary metabolic at different time points before and after drug administration had good similarity within time period and presented clustering phenomenon. Comparing the urine samples of rats before drug administration with which after drug administration, twenty-two metabolites related to brodifacoum-induced toxicity were selected. The toxic effect of brodifacoum worked by disturbing the metabolic pathways in rats such as tricarboxylic cycle, glycolysis, sphingolipid metabolism and tryptophan metabolism, and the toxicity of brodifacoum is characterized of accumulation effect. The metabonomic method based on urine HPLC-TOF-MS can provide a novel insight into the study on molecular mechanism of brodifacoum-induced toxicity. Copyright© by the Editorial Department of Journal of Forensic Medicine

Detection of pH-induced aggregation of "smart" gold nanoparticles with photothermal optical coherence tomography.

PubMed

Xiao, Peng; Li, Qingyun; Joo, Yongjoon; Nam, Jutaek; Hwang, Sekyu; Song, Jaejung; Kim, Sungjee; Joo, Chulmin; Kim, Ki Hean

2013-11-01

We report the feasibility of a novel contrast agent, namely "smart" gold nanoparticles (AuNPs), in the detection of cancer cells with photothermal optical coherence tomography (PT-OCT). "Smart" AuNPs form aggregation in low pH condition, which is typical for cancer cells, and this aggregation results in a shift of their absorption spectrum. A PT-OCT system was developed to detect this pH-induced aggregation by combining an OCT light source and a laser with 660 nm in wavelength for photothermal excitation. Optical detection of pH-induced aggregation was tested with solution samples at two different pH conditions. An increase in optical path length (OPL) variation was measured at mild acidic condition, while there was not much change at neutral condition. Detection of cancer cells was tested with cultured cell samples. HeLa and fibroblast cells, as cancer and normal cells respectively, were incubated with "smart" gold nanoparticles and measured with PT-OCT. An elevated OPL variation signal was detected with the HeLa cells while not much of a signal was detected with the fibroblast cells. With the novel optical property of "smart" AuNPs and high sensitivity of PT-OCT, this technique is promising for cancer cell detection.

Impacts of age and sex on retinal layer thicknesses measured by spectral domain optical coherence tomography with Spectralis.

PubMed

Nieves-Moreno, María; Martínez-de-la-Casa, José M; Morales-Fernández, Laura; Sánchez-Jean, Rubén; Sáenz-Francés, Federico; García-Feijoó, Julián

2018-01-01

To examine differences in individual retinal layer thicknesses measured by spectral domain optical coherence tomography (SD-OCT) (Spectralis®) produced with age and according to sex. Cross-sectional, observational study. The study was conducted in 297 eyes of 297 healthy subjects aged 18 to 87 years. In one randomly selected eye of each participant the volume and mean thicknesses of the different macular layers were measured by SD-OCT using the instrument's macular segmentation software. Volume and mean thickness of macular retinal nerve fiber layer (mRNFL), ganglion cell layer (GCL), inner plexiform layer (IPL), inner nuclear layer (INL), outer plexiform layer (OPL), outer nuclear layer (ONL), retinal pigmentary epithelium (RPE) and photoreceptor layer (PR). Retinal thickness was reduced by 0.24 μm for every one year of age. Age adjusted linear regression analysis revealed mean GCL, IPL, ONL and PR thickness reductions and a mean OPL thickness increase with age. Women had significantly lower mean GCL, IPL, INL, ONL and PR thicknesses and volumes and a significantly greater mRNFL volume than men. The thickness of most retinal layers varies both with age and according to sex. Longitudinal studies are needed to determine the rate of layer thinning produced with age.

Virtual Levels and Role Models: N-Level Structural Equations Model of Reciprocal Ratings Data.

PubMed

Mehta, Paras D

2018-01-01

A general latent variable modeling framework called n-Level Structural Equations Modeling (NL-SEM) for dependent data-structures is introduced. NL-SEM is applicable to a wide range of complex multilevel data-structures (e.g., cross-classified, switching membership, etc.). Reciprocal dyadic ratings obtained in round-robin design involve complex set of dependencies that cannot be modeled within Multilevel Modeling (MLM) or Structural Equations Modeling (SEM) frameworks. The Social Relations Model (SRM) for round robin data is used as an example to illustrate key aspects of the NL-SEM framework. NL-SEM introduces novel constructs such as 'virtual levels' that allows a natural specification of latent variable SRMs. An empirical application of an explanatory SRM for personality using xxM, a software package implementing NL-SEM is presented. Results show that person perceptions are an integral aspect of personality. Methodological implications of NL-SEM for the analyses of an emerging class of contextual- and relational-SEMs are discussed.

Men and women are from Earth: examining the latent structure of gender.

PubMed

Carothers, Bobbi J; Reis, Harry T

2013-02-01

Taxometric methods enable determination of whether the latent structure of a construct is dimensional or taxonic (nonarbitrary categories). Although sex as a biological category is taxonic, psychological gender differences have not been examined in this way. The taxometric methods of mean above minus below a cut, maximum eigenvalue, and latent mode were used to investigate whether gender is taxonic or dimensional. Behavioral measures of stereotyped hobbies and physiological characteristics (physical strength, anthropometric measurements) were examined for validation purposes, and were taxonic by sex. Psychological indicators included sexuality and mating (sexual attitudes and behaviors, mate selectivity, sociosexual orientation), interpersonal orientation (empathy, relational-interdependent self-construal), gender-related dispositions (masculinity, femininity, care orientation, unmitigated communion, fear of success, science inclination, Big Five personality), and intimacy (intimacy prototypes and stages, social provisions, intimacy with best friend). Constructs were with few exceptions dimensional, speaking to Spence's (1993) gender identity theory. Average differences between men and women are not under dispute, but the dimensionality of gender indicates that these differences are inappropriate for diagnosing gender-typical psychological variables on the basis of sex. (c) 2013 APA, all rights reserved.

Metric and structural equivalence of core cognitive abilities measured with the Wechsler Adult Intelligence Scale-III in the United States and Australia.

PubMed

Bowden, Stephen C; Lissner, Dianne; McCarthy, Kerri A L; Weiss, Lawrence G; Holdnack, James A

2007-10-01

Equivalence of the psychological model underlying Wechsler Adult Intelligence Scale-Third Edition (WAIS-III) scores obtained in the United States and Australia was examined in this study. Examination of metric invariance involves testing the hypothesis that all components of the measurement model relating observed scores to latent variables are numerically equal in different samples. The assumption of metric invariance is necessary for interpretation of scores derived from research studies that seek to generalize patterns of convergent and divergent validity and patterns of deficit or disability. An Australian community volunteer sample was compared to the US standardization data. A pattern of strict metric invariance was observed across samples. In addition, when the effects of different demographic characteristics of the US and Australian samples were included, structural parameters reflecting values of the latent cognitive variables were found not to differ. These results provide important evidence for the equivalence of measurement of core cognitive abilities with the WAIS-III and suggest that latent cognitive abilities in the US and Australia do not differ.

Rapid Exploitation and Analysis of Documents

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

Buttler, D J; Andrzejewski, D; Stevens, K D

Analysts are overwhelmed with information. They have large archives of historical data, both structured and unstructured, and continuous streams of relevant messages and documents that they need to match to current tasks, digest, and incorporate into their analysis. The purpose of the READ project is to develop technologies to make it easier to catalog, classify, and locate relevant information. We approached this task from multiple angles. First, we tackle the issue of processing large quantities of information in reasonable time. Second, we provide mechanisms that allow users to customize their queries based on latent topics exposed from corpus statistics. Third,more » we assist users in organizing query results, adding localized expert structure over results. Forth, we use word sense disambiguation techniques to increase the precision of matching user generated keyword lists with terms and concepts in the corpus. Fifth, we enhance co-occurrence statistics with latent topic attribution, to aid entity relationship discovery. Finally we quantitatively analyze the quality of three popular latent modeling techniques to examine under which circumstances each is useful.« less

Further insights on the French WISC-IV factor structure through Bayesian structural equation modeling.

PubMed

Golay, Philippe; Reverte, Isabelle; Rossier, Jérôme; Favez, Nicolas; Lecerf, Thierry

2013-06-01

The interpretation of the Wechsler Intelligence Scale for Children--Fourth Edition (WISC-IV) is based on a 4-factor model, which is only partially compatible with the mainstream Cattell-Horn-Carroll (CHC) model of intelligence measurement. The structure of cognitive batteries is frequently analyzed via exploratory factor analysis and/or confirmatory factor analysis. With classical confirmatory factor analysis, almost all cross-loadings between latent variables and measures are fixed to zero in order to allow the model to be identified. However, inappropriate zero cross-loadings can contribute to poor model fit, distorted factors, and biased factor correlations; most important, they do not necessarily faithfully reflect theory. To deal with these methodological and theoretical limitations, we used a new statistical approach, Bayesian structural equation modeling (BSEM), among a sample of 249 French-speaking Swiss children (8-12 years). With BSEM, zero-fixed cross-loadings between latent variables and measures are replaced by approximate zeros, based on informative, small-variance priors. Results indicated that a direct hierarchical CHC-based model with 5 factors plus a general intelligence factor better represented the structure of the WISC-IV than did the 4-factor structure and the higher order models. Because a direct hierarchical CHC model was more adequate, it was concluded that the general factor should be considered as a breadth rather than a superordinate factor. Because it was possible for us to estimate the influence of each of the latent variables on the 15 subtest scores, BSEM allowed improvement of the understanding of the structure of intelligence tests and the clinical interpretation of the subtest scores. PsycINFO Database Record (c) 2013 APA, all rights reserved.

High-Dimensional Sparse Factor Modeling: Applications in Gene Expression Genomics

PubMed Central

Carvalho, Carlos M.; Chang, Jeffrey; Lucas, Joseph E.; Nevins, Joseph R.; Wang, Quanli; West, Mike

2010-01-01

We describe studies in molecular profiling and biological pathway analysis that use sparse latent factor and regression models for microarray gene expression data. We discuss breast cancer applications and key aspects of the modeling and computational methodology. Our case studies aim to investigate and characterize heterogeneity of structure related to specific oncogenic pathways, as well as links between aggregate patterns in gene expression profiles and clinical biomarkers. Based on the metaphor of statistically derived “factors” as representing biological “subpathway” structure, we explore the decomposition of fitted sparse factor models into pathway subcomponents and investigate how these components overlay multiple aspects of known biological activity. Our methodology is based on sparsity modeling of multivariate regression, ANOVA, and latent factor models, as well as a class of models that combines all components. Hierarchical sparsity priors address questions of dimension reduction and multiple comparisons, as well as scalability of the methodology. The models include practically relevant non-Gaussian/nonparametric components for latent structure, underlying often quite complex non-Gaussianity in multivariate expression patterns. Model search and fitting are addressed through stochastic simulation and evolutionary stochastic search methods that are exemplified in the oncogenic pathway studies. Supplementary supporting material provides more details of the applications, as well as examples of the use of freely available software tools for implementing the methodology. PMID:21218139

Assessing the fit of the Dysphoric Arousal model across two nationally representative epidemiological surveys: The Australian NSMHWB and the United States NESARC.

PubMed

Armour, Cherie; Carragher, Natacha; Elhai, Jon D

2013-01-01

Since the initial inclusion of PTSD in the DSM nomenclature, PTSD symptomatology has been distributed across three symptom clusters. However, a wealth of empirical research has concluded that PTSD's latent structure is best represented by one of two four-factor models: Numbing or Dysphoria. Recently, a newly proposed five-factor Dysphoric Arousal model, which separates the DSM-IV's Arousal cluster into two factors of Anxious Arousal and Dysphoric Arousal, has gathered support across a variety of trauma samples. To date, the Dysphoric Arousal model has not been assessed using nationally representative epidemiological data. We employed confirmatory factor analysis to examine PTSD's latent structure in two independent population based surveys from American (NESARC) and Australia (NSWHWB). We specified and estimated the Numbing model, the Dysphoria model, and the Dysphoric Arousal model in both samples. Results revealed that the Dysphoric Arousal model provided superior fit to the data compared to the alternative models. In conclusion, these findings suggest that items D1-D3 (sleeping difficulties; irritability; concentration difficulties) represent a separate, fifth factor within PTSD's latent structure using nationally representative epidemiological data in addition to single trauma specific samples. Copyright © 2012 Elsevier Ltd. All rights reserved.

What Types of Pornography Do People Find Arousing and Do They Cluster? Assessing Types and Categories of Pornography in a Large-Scale Online Sample.

PubMed

Hald, Gert Martin; Štulhofer, Aleksandar

2016-09-01

Previous research on exposure to different types of pornography has primarily relied on analyses of millions of search terms and histories or on user exposure patterns within a given time period rather than the self-reported frequency of consumption. Further, previous research has almost exclusively relied on theoretical or ad hoc overarching categorizations of different types of pornography, when investigating patterns of pornography exposure, rather than latent structure analyses of these exposure patterns. In contrast, using a large sample of 18- to 40-year-old heterosexual and nonheterosexual Croatian men and women, this study investigated the self-reported frequency of using 27 different types of pornography and statistically explored their latent structures. The results showed substantial differences in consumption patterns across gender and sexual orientation. However, latent structure analyses of the 27 different types of pornography assessed suggested that although several categories of consumption were gender and sexual orientation specific, common categories across the different types of pornography could be established. Based on this finding, a five-item scale was proposed to indicate the use of nonmainstream (paraphilic) pornographic content, as this type of pornography has often been targeted in previous research. To the best of our knowledge, no similar measurement tool has been proposed before.

Intra-Sensor Variability Study of two BLS 900 Scintillometers

NASA Astrophysics Data System (ADS)

Thiem, Christina; Mauder, Matthias; Chwala, Christian; Bernhardt, Matthias; Kunstmann, Harald; Schulz, Karsten

2017-04-01

The latent heat flux is an important validation parameter for satellite measurements and a wide variety of hydrological and meteorological numerical models. Scintillometers can provide references for such validations due to their ability to spatially integrate turbulent fluxes. Large-aperture near-infrared scintillometers are capable of determining spatial averages of the structure parameter of temperature and the sensible heat flux over path lengths up to 5 km. One way to derive both sensible and latent heat flux is to use a combined optical and microwave scintillometer system. With only an optical scintillometer and additional measurements of ground heat flux and net radiation, the latent heat flux can be calculated from the residual of the energy balance. Studies have shown, however, that in certain cases measurements from the same types of scintillometers differ due to minute differences in construction. In order to prove the robustness of the measurements of two near-infrared scintillometers for future studies, we compared their observations and validated them by comparison to the sensible heat flux derived from an eddy covariance system. In this study two boundary layer scintillometers (BLS; BLS900, Scintec, Rottenburg, Germany) were installed in a central European valley as part of the TERENO preAlpine observatory during the years 2013 and 2015. An independent measurement of the sensible and latent heat flux was obtained from a permanent eddy covariance system installed in the vicinity of the scintillometer path. The structure parameter of the refractive index and average sensible heat fluxes of both BLS units were compared with each other. In general, the BLS structure parameters correlated very well and the high correlation between the BLS-derived sensible heat fluxes and the eddy covariance-derived sensible heat fluxes encouraged further application of these scintillometers in separate experiments.

Molecular dynamics simulations of shock waves in hydroxyl-terminated polybutadiene melts: Mechanical and structural responses

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

Fröhlich, Markus G., E-mail: FroehlichM@missouri.edu, E-mail: ThompsonDon@missouri.edu; Sewell, Thomas D., E-mail: SewellT@missouri.edu; Thompson, Donald L., E-mail: FroehlichM@missouri.edu, E-mail: ThompsonDon@missouri.edu

2014-01-14

The mechanical and structural responses of hydroxyl-terminated cis-1,4-polybutadiene melts to shock waves were investigated by means of all-atom non-reactive molecular dynamics simulations. The simulations were performed using the OPLS-AA force field but with the standard 12-6 Lennard-Jones potential replaced by the Buckingham exponential-6 potential to better represent the interactions at high compression. Monodisperse systems containing 64, 128, and 256 backbone carbon atoms were studied. Supported shock waves were generated by impacting the samples onto stationary pistons at impact velocities of 1.0, 1.5, 2.0, and 2.5 km s{sup −1}, yielding shock pressures between approximately 2.8 GPa and 12.5 GPa. Single-molecule structuralmore » properties (squared radii of gyration, asphericity parameters, and orientational order parameters) and mechanical properties (density, shock pressure, shock temperature, and shear stress) were analyzed using a geometric binning scheme to obtain spatio-temporal resolution in the reference frame centered on the shock front. Our results indicate that while shear stress behind the shock front is relieved on a ∼0.5 ps time scale, a shock-induced transition to a glass-like state occurs with a concomitant increase of structural relaxation times by several orders of magnitude.« less

Structural equation models to estimate risk of infection and tolerance to bovine mastitis.

PubMed

Detilleux, Johann; Theron, Léonard; Duprez, Jean-Noël; Reding, Edouard; Humblet, Marie-France; Planchon, Viviane; Delfosse, Camille; Bertozzi, Carlo; Mainil, Jacques; Hanzen, Christian

2013-03-06

One method to improve durably animal welfare is to select, as reproducers, animals with the highest ability to resist or tolerate infection. To do so, it is necessary to distinguish direct and indirect mechanisms of resistance and tolerance because selection on these traits is believed to have different epidemiological and evolutionary consequences. We propose structural equation models with latent variables (1) to quantify the latent risk of infection and to identify, among the many potential mediators of infection, the few ones that influence it significantly and (2) to estimate direct and indirect levels of tolerance of animals infected naturally with pathogens. We applied the method to two surveys of bovine mastitis in the Walloon region of Belgium, in which we recorded herd management practices, mastitis frequency, and results of bacteriological analyses of milk samples. Structural equation models suggested that, among more than 35 surveyed herd characteristics, only nine (age, addition of urea in the rations, treatment of subclinical mastitis, presence of dirty liner, cows with hyperkeratotic teats, machine stripping, pre- and post-milking teat disinfection, and housing of milking cows in cubicles) were directly and significantly related to a latent measure of bovine mastitis, and that treatment of subclinical mastitis was involved in the pathway between post-milking teat disinfection and latent mastitis. These models also allowed the separation of direct and indirect effects of bacterial infection on milk productivity. Results suggested that infected cows were tolerant but not resistant to mastitis pathogens. We revealed the advantages of structural equation models, compared to classical models, for dissecting measurements of resistance and tolerance to infectious diseases, here bovine mastitis. Using our method, we identified nine major risk factors that were directly associated with an increased risk of mastitis and suggested that cows were tolerant but not resistant to mastitis. Selection should aim at improved resistance to infection by mastitis pathogens, although further investigations are needed due to the limitations of the data used in this study.

Cross-domain latent space projection for person re-identification

NASA Astrophysics Data System (ADS)

Pu, Nan; Wu, Song; Qian, Li; Xiao, Guoqiang

2018-04-01

In this paper, we research the problem of person re-identification and propose a cross-domain latent space projection (CDLSP) method to address the problems of the absence or insufficient labeled data in the target domain. Under the assumption that the visual features in the source domain and target domain share the similar geometric structure, we transform the visual features from source domain and target domain to a common latent space by optimizing the object function defined in the manifold alignment method. Moreover, the proposed object function takes into account the specific knowledge in the re-id with the aim to improve the performance of re-id under complex situations. Extensive experiments conducted on four benchmark datasets show the proposed CDLSP outperforms or is competitive with stateof- the-art methods for person re-identification.

About the structural role of disulfide bridges in serum albumins: evidence from protein simulated unfolding.

PubMed

Paris, Guillaume; Kraszewski, Sebastian; Ramseyer, Christophe; Enescu, Mironel

2012-11-01

The role of the 17 disulfide (S-S) bridges in preserving the native conformation of human serum albumin (HSA) is investigated by performing classical molecular dynamics (MD) simulations on protein structures with intact and, respectively, reduced S-S bridges. The thermal unfolding simulations predict a clear destabilization of the protein secondary structure upon reduction of the S-S bridges as well as a significant distortion of the tertiary structure that is revealed by the changes in the protein native contacts fraction. The effect of the S-S bridges reduction on the protein compactness was tested by calculating Gibbs free energy profiles with respect to the protein gyration radius. The theoretical results obtained using the OPLS-AA and the AMBER ff03 force fields are in agreement with the available experimental data. Beyond the validation of the simulation method, the results here reported provide new insights into the mechanism of the protein reductive/oxidative unfolding/folding processes. It is predicted that in the native conformation of the protein, the thiol (-SH) groups belonging to the same reduced S-S bridge are located in potential wells that maintain them in contact. The -SH pairs can be dispatched by specific conformational transitions of the peptide chain located in the neighborhood of the cysteine residues. Copyright © 2012 Wiley Periodicals, Inc.

Effects of different force fields on the structural character of α synuclein β-hairpin peptide (35-56) in aqueous environment.

PubMed

Kundu, Sangeeta

2018-02-01

The hallmark of Parkinson's disease (PD) is the intracellular protein aggregation forming Lewy Bodies (LB) and Lewy neuritis which comprise mostly of a protein, alpha synuclein (α-syn). Molecular dynamics (MD) simulation methods can augment experimental techniques to understand misfolding and aggregation pathways with atomistic resolution. The quality of MD simulations for proteins and peptides depends greatly on the accuracy of empirical force fields. The aim of this work is to investigate the effects of different force fields on the structural character of β hairpin fragment of α-syn (residues 35-56) peptide in aqueous solution. Six independent MD simulations are done in explicit solvent using, AMBER03, AMBER99SB, GROMOS96 43A1, GROMOS96 53A6, OPLS-AA, and CHARMM27 force fields with CMAP corrections. The performance of each force field is assessed from several structural parameters such as root mean square deviation (RMSD), root mean square fluctuation (RMSF), radius of gyration (Rg), solvent accessible surface area (SASA), formation of β-turn, the stability of folded β-hairpin structure, and the favourable conformations obtained for different force fields. In this study, CMAP correction of CHARMM27 force field is found to overestimate the helical conformation, while GROMOS96 53A6 is found to most successfully capture the conformational dynamics of α-syn β-hairpin fragment as elicited from NMR.

Models of Latent Tuberculosis: Their Salient Features, Limitations, and Development

PubMed Central

Patel, Kamlesh; Jhamb, Sarbjit Singh; Singh, Prati Pal

2011-01-01

Latent tuberculosis is a subclinical condition caused by Mycobacterium tuberculosis, which affects about one-third of the population across the world. To abridge the chemotherapy of tuberculosis, it is necessary to have active drugs against latent form of M. tuberculosis. Therefore, it is imperative to devise in vitro and models of latent tuberculosis to explore potential drugs. In vitro models such as hypoxia, nutrient starvation, and multiple stresses are based on adverse conditions encountered by bacilli in granuloma. Bacilli experience oxygen depletion condition in hypoxia model, whereas the nutrient starvation model is based on deprivation of total nutrients from a culture medium. In the multiple stress model dormancy is induced by more than one type of stress. In silico mathematical models have also been developed to predict the interactions of bacilli with the host immune system and to propose structures for potential anti tuberculosis compounds. Besides these in vitro and in silico models, there are a number of in vivo animal models like mouse, guinea pig, rabbit, etc. Although they simulate human latent tuberculosis up to a certain extent but do not truly replicate human infection. All these models have their inherent merits and demerits. However, there is no perfect model for latent tuberculosis. Therefore, it is imperative to upgrade and refine existing models or develop a new model. However, battery of models will always be a better alternative to any single model as they will complement each other by overcoming their limitations. PMID:22219558

Detection of latent fingerprint hidden beneath adhesive tape by optical coherence tomography.

PubMed

Zhang, Ning; Wang, Chengming; Sun, Zhenwen; Li, Zhigang; Xie, Lanchi; Yan, Yuwen; Xu, Lei; Guo, Jingjing; Huang, Wei; Li, Zhihui; Xue, Jing; Liu, Huan; Xu, Xiaojing

2018-06-01

Adhesive tape is one type of common item which can be encountered in criminal cases involving rape, murder, kidnapping and explosives. It is often the case that a suspect deposits latent fingerprints on the sticky side of adhesive tape material when tying up victims, manufacturing improvised explosive devices or packaging illegal goods. However, the adhesive tapes found at crime scenes are usually stuck together or attached to a certain substrate, and thus the latent fingerprints may be hidden beneath the tapes. Current methods to detect latent fingerprint hidden beneath adhesive tape need to peel it off first and then apply physical or chemical methods to develop the fingerprint, which undergo complicated procedures and would affect the original condition of latent print. Optical coherence tomography (OCT) is a novel applied techniques in forensics which enables obtaining cross-sectional structure with the advantages of non-invasive, in-situ, high resolution and high speed. In this paper, a custom-built spectral-domain OCT (SD-OCT) system with a hand-held probe was employed to detect fingerprints hidden beneath different types of adhesive tapes. Three-dimensional (3D) OCT reconstructions were performed and the en face images were presented to reveal the hidden fingerprints. The results demonstrate that OCT is a promising tool for rapidly detecting and recovering high quality image of latent fingerprint hidden beneath adhesive tape without any changes to the original state and preserve the integrity of the evidence. Copyright © 2018 Elsevier B.V. All rights reserved.

The job content questionnaire in various occupational contexts: applying a latent class model

PubMed Central

Santos, Kionna Oliveira Bernardes; de Araújo, Tânia Maria; Karasek, Robert

2017-01-01

Objective To evaluate Job Content Questionnaire(JCQ) performance using the latent class model. Methods We analysed cross-sectional studies conducted in Brazil and examined three occupational categories: petroleum industry workers (n=489), teachers (n=4392) and primary healthcare workers (3078)and 1552 urban workers from a representative sample of the city of Feira de Santana in Bahia, Brazil. An appropriate number of latent classes was extracted and described each occupational category using latent class analysis, a multivariate method that evaluates constructs and takes into account the latent characteristics underlying the structure of measurement scales. The conditional probabilities of workers belonging to each class were then analysed graphically. Results Initially, the latent class analysis extracted four classes corresponding to the four job types (active, passive, low strain and high strain) proposed by the Job-Strain model (JSM) and operationalised by the JCQ. However, after taking into consideration the adequacy criteria to evaluate the number of extracted classes, three classes (active, low strain and high strain) were extracted from the studies of urban workers and teachers and four classes (active, passive, low strain and high strain) from the study of primary healthcare and petroleum industry workers. Conclusion The four job types proposed by the JSM were identified among primary healthcare and petroleum industry workers—groups with relatively high levels of skill discretion and decision authority. Three job types were identified for teachers and urban workers; however, passive job situations were not found within these groups. The latent class analysis enabled us to describe the conditional standard responses of the job types proposed by the model, particularly in relation to active jobs and high and low strain situations. PMID:28515185

Aggressiveness as a latent personality trait of domestic dogs: Testing local independence and measurement invariance.

PubMed

Goold, Conor; Newberry, Ruth C

2017-01-01

Studies of animal personality attempt to uncover underlying or "latent" personality traits that explain broad patterns of behaviour, often by applying latent variable statistical models (e.g., factor analysis) to multivariate data sets. Two integral, but infrequently confirmed, assumptions of latent variable models in animal personality are: i) behavioural variables are independent (i.e., uncorrelated) conditional on the latent personality traits they reflect (local independence), and ii) personality traits are associated with behavioural variables in the same way across individuals or groups of individuals (measurement invariance). We tested these assumptions using observations of aggression in four age classes (4-10 months, 10 months-3 years, 3-6 years, over 6 years) of male and female shelter dogs (N = 4,743) in 11 different contexts. A structural equation model supported the hypothesis of two positively correlated personality traits underlying aggression across contexts: aggressiveness towards people and aggressiveness towards dogs (comparative fit index: 0.96; Tucker-Lewis index: 0.95; root mean square error of approximation: 0.03). Aggression across contexts was moderately repeatable (towards people: intraclass correlation coefficient (ICC) = 0.479; towards dogs: ICC = 0.303). However, certain contexts related to aggressiveness towards people (but not dogs) shared significant residual relationships unaccounted for by latent levels of aggressiveness. Furthermore, aggressiveness towards people and dogs in different contexts interacted with sex and age. Thus, sex and age differences in displays of aggression were not simple functions of underlying aggressiveness. Our results illustrate that the robustness of traits in latent variable models must be critically assessed before making conclusions about the effects of, or factors influencing, animal personality. Our findings are of concern because inaccurate "aggressive personality" trait attributions can be costly to dogs, recipients of aggression and society in general.

Incorporating Value Systems in Strategic Force Analysis

DTIC Science & Technology

1991-03-01

produce Typhoon and Delta IV class submarines. Other indications of the questionable intentions of the Soviet military machine are in allegations...Communications, their energy systems, transpcrtation, defense, oil, chemical, electronic, machine building and instruments industries, their reserves and...HAD100 8 -4 Transp . 1200 .4 SOCEc 3 opl.700 .17 .1In.1000 .14 Mild EO. 1Pr Warfighting . -8Fo 2000 .56 W8aoo 1000 .14 Tagt 1Id. 700 .11 StrutureSUPPT

Insights into unbound-bound states of GPR142 receptor in a membrane-aqueous system using molecular dynamics simulations.

PubMed

Kaushik, Aman Chandra; Sahi, Shakti

2018-05-01

G protein coupled receptors (GPCRs) are source machinery in signal transduction pathways and being one of the major therapeutic targets play a significant in drug discovery. GPR142, an orphan GPCR, has been implicated in the regulation of insulin, thereby having a crucial role in Type II diabetes management. Deciphering of the structures of orphan, GPCRs (O-GPCRs) offer better prospects for advancements in research in ion translocation and transduction of extracellular signals. As the crystallographic structure of GPR142 is not available in PDB, therefore, threading and ab initio-based approaches were used for 3D modeling of GPR142. Molecular dynamic simulations (900 ns) were performed on the 3D model of GPR142 and complexes of GPR142 with top five hits, obtained through virtual screening, embedded in lipid bilayer with aqueous system using OPLS force field. Compound 1, 3, and 4 may act as scaffolds for designing potential lead agonists for GPR142. The finding of GPR142 MD simulation study provides more comprehensive representation of the functional properties. The concern for Type II diabetes is increasing worldwide and successful treatment of this disease demands novel drugs with better efficacy.

White-emissive tandem-type hybrid organic/polymer diodes with (0.33, 0.33) chromaticity coordinates.

PubMed

Guo, Tzung-Fang; Wen, Ten-Chin; Huang, Yi-Shun; Lin, Ming-Wei; Tsou, Chuan-Cheng; Chung, Chia-Tin

2009-11-09

This study reports fabrication of white-emissive, tandem-type, hybrid organic/polymer light-emitting diodes (O/PLED). The tandem devices are made by stacking a blue-emissive OLED on a yellow-emissive phenyl-substituted poly(para-phenylene vinylene) copolymer-based PLED and applying an organic oxide/Al/molybdenum oxide (MoO(3)) complex structure as a connecting structure or charge-generation layer (CGL). The organic oxide/Al/MoO(3) CGL functions as an effective junction interface for the transport and injection of opposite charge carriers through the stacked configuration. The electroluminescence (EL) spectra of the tandem-type devices can be tuned by varying the intensity of the emission in each emissive component to yield the visible-range spectra from 400 to 750 nm, with Commission Internationale de l'Eclairage chromaticity coordinates of (0.33, 0.33) and a high color rendering capacity as used for illumination. The EL spectra also exhibit good color stability under various bias conditions. The tandem-type device of emission with chromaticity coordinates, (0.30, 0.31), has maximum brightness and luminous efficiency over 25,000 cd/m(2) and approximately 4.2 cd/A, respectively.

Maximum Likelihood Analysis of Nonlinear Structural Equation Models with Dichotomous Variables

ERIC Educational Resources Information Center

Song, Xin-Yuan; Lee, Sik-Yum

2005-01-01

In this article, a maximum likelihood approach is developed to analyze structural equation models with dichotomous variables that are common in behavioral, psychological and social research. To assess nonlinear causal effects among the latent variables, the structural equation in the model is defined by a nonlinear function. The basic idea of the…

Understanding the Latent Structure of the Emotional Disorders in Children and Adolescents

ERIC Educational Resources Information Center

Trosper, Sarah E.; Whitton, Sarah W.; Brown, Timothy A.; Pincus, Donna B.

2012-01-01

Investigators are persistently aiming to clarify structural relationships among the emotional disorders in efforts to improve diagnostic classification. The high co-occurrence of anxiety and mood disorders, however, has led investigators to portray the current structure of anxiety and depression in the "Diagnostic and Statistical Manual of Mental…

Study on TCM Syndrome Differentiation of Primary Liver Cancer Based on the Analysis of Latent Structural Model.

PubMed

Gu, Zhan; Qi, Xiuzhong; Zhai, Xiaofeng; Lang, Qingbo; Lu, Jianying; Ma, Changping; Liu, Long; Yue, Xiaoqiang

2015-01-01

Primary liver cancer (PLC) is one of the most common malignant tumors because of its high incidence and high mortality. Traditional Chinese medicine (TCM) plays an active role in the treatment of PLC. As the most important part in the TCM system, syndrome differentiation based on the clinical manifestations from traditional four diagnostic methods has met great challenges and questions with the lack of statistical validation support. In this study, we provided evidences for TCM syndrome differentiation of PLC using the method of analysis of latent structural model from clinic data, thus providing basis for establishing TCM syndrome criteria. And also we obtain the common syndromes of PLC as well as their typical clinical manifestations, respectively.

Three Cs in measurement models: causal indicators, composite indicators, and covariates.

PubMed

Bollen, Kenneth A; Bauldry, Shawn

2011-09-01

In the last 2 decades attention to causal (and formative) indicators has grown. Accompanying this growth has been the belief that one can classify indicators into 2 categories: effect (reflective) indicators and causal (formative) indicators. We argue that the dichotomous view is too simple. Instead, there are effect indicators and 3 types of variables on which a latent variable depends: causal indicators, composite (formative) indicators, and covariates (the "Three Cs"). Causal indicators have conceptual unity, and their effects on latent variables are structural. Covariates are not concept measures, but are variables to control to avoid bias in estimating the relations between measures and latent variables. Composite (formative) indicators form exact linear combinations of variables that need not share a concept. Their coefficients are weights rather than structural effects, and composites are a matter of convenience. The failure to distinguish the Three Cs has led to confusion and questions, such as, Are causal and formative indicators different names for the same indicator type? Should an equation with causal or formative indicators have an error term? Are the coefficients of causal indicators less stable than effect indicators? Distinguishing between causal and composite indicators and covariates goes a long way toward eliminating this confusion. We emphasize the key role that subject matter expertise plays in making these distinctions. We provide new guidelines for working with these variable types, including identification of models, scaling latent variables, parameter estimation, and validity assessment. A running empirical example on self-perceived health illustrates our major points.

Development of a Coarse-grained Model of Polypeptoids for Studying Self-assembly in Solution

NASA Astrophysics Data System (ADS)

Du, Pu; Rick, Steven; Kumar, Revati

Polypeptoid, a class of highly tunable biomimetic analogues of peptides, are used as a prototypical model system to study self-assembly. The focus of this work is to glean insight into the effect of electrostatic and other non-covalent secondary interactions on the self-assembly of sequence-defined polypeptoids, with different charged and uncharged side groups, in solution that will complement experiments. Atomistic (AA) molecular dynamics simulation can provide a complete description of self-assembly of polypeptoid systems. However, the long simulation length and time scales needed for these processes require the development of a computationally cheaper alternative, namely coarse-grained (CG) models. A CG model for studying polypeptoid micellar interactions is being developed, parameterized on atomistic simulations, using a hybridized approach involving the OPLS-UA force filed and the Stillinger-Weber (SW) potential form. The development of the model as well as the results from the simulations on the self-assembly as function of polypeptoid chemical structure and sequences will be presented.

Investigating the Theoretical Structure of the DAS-II Core Battery at School Age Using Bayesian Structural Equation Modeling

ERIC Educational Resources Information Center

Dombrowski, Stefan C.; Golay, Philippe; McGill, Ryan J.; Canivez, Gary L.

2018-01-01

Bayesian structural equation modeling (BSEM) was used to investigate the latent structure of the Differential Ability Scales-Second Edition core battery using the standardization sample normative data for ages 7-17. Results revealed plausibility of a three-factor model, consistent with publisher theory, expressed as either a higher-order (HO) or a…

Utilizing the Structure and Content Information for XML Document Clustering

NASA Astrophysics Data System (ADS)

Tran, Tien; Kutty, Sangeetha; Nayak, Richi

This paper reports on the experiments and results of a clustering approach used in the INEX 2008 document mining challenge. The clustering approach utilizes both the structure and content information of the Wikipedia XML document collection. A latent semantic kernel (LSK) is used to measure the semantic similarity between XML documents based on their content features. The construction of a latent semantic kernel involves the computing of singular vector decomposition (SVD). On a large feature space matrix, the computation of SVD is very expensive in terms of time and memory requirements. Thus in this clustering approach, the dimension of the document space of a term-document matrix is reduced before performing SVD. The document space reduction is based on the common structural information of the Wikipedia XML document collection. The proposed clustering approach has shown to be effective on the Wikipedia collection in the INEX 2008 document mining challenge.

Insight into the microscopic structure of an AdS black hole from a thermodynamical phase transition.

PubMed

Wei, Shao-Wen; Liu, Yu-Xiao

2015-09-11

Comparing with an ordinary thermodynamic system, we investigate the possible microscopic structure of a charged anti-de Sitter black hole completely from the thermodynamic viewpoint. The number density of the black hole molecules is introduced to measure the microscopic degrees of freedom of the black hole. We found that the number density suffers a sudden change accompanied by a latent heat when the black hole system crosses the small-large black hole coexistence curve, while when the system passes the critical point, it encounters a second-order phase transition with a vanishing latent heat due to the continuous change of the number density. Moreover, the thermodynamic scalar curvature suggests that there is a weak attractive interaction between two black hole molecules. These phenomena might cast new insight into the underlying microscopic structure of a charged anti-de Sitter black hole.

A comparison of latent class, K-means, and K-median methods for clustering dichotomous data.

PubMed

Brusco, Michael J; Shireman, Emilie; Steinley, Douglas

2017-09-01

The problem of partitioning a collection of objects based on their measurements on a set of dichotomous variables is a well-established problem in psychological research, with applications including clinical diagnosis, educational testing, cognitive categorization, and choice analysis. Latent class analysis and K-means clustering are popular methods for partitioning objects based on dichotomous measures in the psychological literature. The K-median clustering method has recently been touted as a potentially useful tool for psychological data and might be preferable to its close neighbor, K-means, when the variable measures are dichotomous. We conducted simulation-based comparisons of the latent class, K-means, and K-median approaches for partitioning dichotomous data. Although all 3 methods proved capable of recovering cluster structure, K-median clustering yielded the best average performance, followed closely by latent class analysis. We also report results for the 3 methods within the context of an application to transitive reasoning data, in which it was found that the 3 approaches can exhibit profound differences when applied to real data. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

The NEO Five-Factor Inventory: latent structure and relationships with dimensions of anxiety and depressive disorders in a large clinical sample.

PubMed

Rosellini, Anthony J; Brown, Timothy A

2011-03-01

The present study evaluated the latent structure of the NEO Five-Factor Inventory (NEO FFI) and relations between the five-factor model (FFM) of personality and dimensions of DSM-IV anxiety and depressive disorders (panic disorder, generalized anxiety disorder [GAD], obsessive-compulsive disorder, social phobia [SOC], major depressive disorder [MDD]) in a large sample of outpatients (N = 1,980). Exploratory structural equation modeling (ESEM) was used to show that a five-factor solution provided acceptable model fit, albeit with some poorly functioning items. Neuroticism demonstrated significant positive associations with all but one of the disorder constructs whereas Extraversion was inversely related to SOC and MDD. Conscientiousness was inversely related to MDD but demonstrated a positive relationship with GAD. Results are discussed in regard to potential revisions to the NEO FFI, the evaluation of other NEO instruments using ESEM, and clinical implications of structural paths between FFM domains and specific emotional disorders.

The NEO Five-Factor Inventory: Latent Structure and Relationships With Dimensions of Anxiety and Depressive Disorders in a Large Clinical Sample

PubMed Central

Rosellini, Anthony J.; Brown, Timothy A.

2017-01-01

The present study evaluated the latent structure of the NEO Five-Factor Inventory (NEO FFI) and relations between the five-factor model (FFM) of personality and dimensions of DSM-IV anxiety and depressive disorders (panic disorder, generalized anxiety disorder [GAD], obsessive–compulsive disorder, social phobia [SOC], major depressive disorder [MDD]) in a large sample of outpatients (N = 1,980). Exploratory structural equation modeling (ESEM) was used to show that a five-factor solution provided acceptable model fit, albeit with some poorly functioning items. Neuroticism demonstrated significant positive associations with all but one of the disorder constructs whereas Extraversion was inversely related to SOC and MDD. Conscientiousness was inversely related to MDD but demonstrated a positive relationship with GAD. Results are discussed in regard to potential revisions to the NEO FFI, the evaluation of other NEO instruments using ESEM, and clinical implications of structural paths between FFM domains and specific emotional disorders. PMID:20881102

An investigation of the marine boundary layer during cold air outbreak

NASA Technical Reports Server (NTRS)

Stage, S. A.

1986-01-01

Methods for use in the remote estimation of ocean surface sensible and latent heat fluxes were developed and evaluated. Three different techniques were developed for determining these fluxes. These methods are: (1) Obtaining surface sensible and latent heat fluxes from satellite measurements; (2)Obtaining surface sensible and latent heat fluxes from an MABL model; (3) A method using horizontal transfer coefficients. These techniques are not very sensitive to errors in the data and therefore appear to hold promise of producing useful answers. Questions remain about how closely the structure of the real atmosphere agrees with the assumptions made for each of these techniques, and, therefore about how well these techniques can perform in actual use. The value of these techniques is that they promise to provide methods for the determination of fluxes over regions where very few traditional measurement exist.

Modeling and impacts of the latent heat of phase change and specific heat for phase change materials

NASA Astrophysics Data System (ADS)

Scoggin, J.; Khan, R. S.; Silva, H.; Gokirmak, A.

2018-05-01

We model the latent heats of crystallization and fusion in phase change materials with a unified latent heat of phase change, ensuring energy conservation by coupling the heat of phase change with amorphous and crystalline specific heats. We demonstrate the model with 2-D finite element simulations of Ge2Sb2Te5 and find that the heat of phase change increases local temperature up to 180 K in 300 nm × 300 nm structures during crystallization, significantly impacting grain distributions. We also show in electrothermal simulations of 45 nm confined and 10 nm mushroom cells that the higher amorphous specific heat predicted by this model increases nucleation probability at the end of reset operations. These nuclei can decrease set time, leading to variability, as demonstrated for the mushroom cell.

Morphological Diversity of the Rod Spherule: A Study of Serially Reconstructed Electron Micrographs

PubMed Central

Li, Shuai; Mitchell, Joe; Briggs, Deidrie J.; Young, Jaime K.; Long, Samuel S.; Fuerst, Peter G.

2016-01-01

Purpose Rod spherules are the site of the first synaptic contact in the retina’s rod pathway, linking rods to horizontal and bipolar cells. Rod spherules have been described and characterized through electron micrograph (EM) and other studies, but their morphological diversity related to retinal circuitry and their intracellular structures have not been quantified. Most rod spherules are connected to their soma by an axon, but spherules of rods on the surface of the Mus musculus outer plexiform layer often lack an axon and have a spherule structure that is morphologically distinct from rod spherules connected to their soma by an axon. Retraction of the rod axon and spherule is often observed in disease processes and aging, and the retracted rod spherule superficially resembles rod spherules lacking an axon. We hypothesized that retracted spherules take on an axonless spherule morphology, which may be easier to maintain in a diseased state. To test our hypothesis, we quantified the spatial organization and subcellular structures of rod spherules with and without axons. We then compared them to the retracted spherules in a disease model, mice that overexpress Dscam (Down syndrome cell adhesion molecule), to gain a better understanding of the rod synapse in health and disease. Methods We reconstructed serial EM images of wild type and DscamGoF (gain of function) rod spherules at a resolution of 7 nm in the X-Y axis and 60 nm in the Z axis. Rod spherules with and without axons, and retracted spherules in the DscamGoF retina, were reconstructed. The rod spherule intracellular organelles, the invaginating dendrites of rod bipolar cells and horizontal cell axon tips were also reconstructed for statistical analysis. Results Stereotypical rod (R1) spherules occupy the outer two-thirds of the outer plexiform layer (OPL), where they present as spherical terminals with large mitochondria. This spherule group is highly uniform and composed more than 90% of the rod spherule population. Rod spherules lacking an axon (R2) were also described and characterized. This rod spherule group consists of a specific spatial organization that is strictly located at the apical OPL-facing layer of the Outer Nuclear Layer (ONL). The R2 spherule displays a large bowl-shaped synaptic terminal that hugs the rod soma. Retracted spherules in the DscamGoF retina were also reconstructed to test if they are structurally similar to R2 spherules. The misplaced rod spherules in DscamGoF have a gross morphology that is similar to R2 spherules but have significant disruption in internal synapse organization. Conclusion We described a morphological diversity within Mus musculus rod spherules. This diversity is correlated with rod location in the ONL and contributes to the intracellular differences within spherules. Analysis of the DscamGoF retina indicated that their R2 spherules are not significantly different than wild type R2 spherules, but that their retracted rod spherules have abnormal synaptic organization. PMID:26930660

Morphological Diversity of the Rod Spherule: A Study of Serially Reconstructed Electron Micrographs.

PubMed

Li, Shuai; Mitchell, Joe; Briggs, Deidrie J; Young, Jaime K; Long, Samuel S; Fuerst, Peter G

2016-01-01

Rod spherules are the site of the first synaptic contact in the retina's rod pathway, linking rods to horizontal and bipolar cells. Rod spherules have been described and characterized through electron micrograph (EM) and other studies, but their morphological diversity related to retinal circuitry and their intracellular structures have not been quantified. Most rod spherules are connected to their soma by an axon, but spherules of rods on the surface of the Mus musculus outer plexiform layer often lack an axon and have a spherule structure that is morphologically distinct from rod spherules connected to their soma by an axon. Retraction of the rod axon and spherule is often observed in disease processes and aging, and the retracted rod spherule superficially resembles rod spherules lacking an axon. We hypothesized that retracted spherules take on an axonless spherule morphology, which may be easier to maintain in a diseased state. To test our hypothesis, we quantified the spatial organization and subcellular structures of rod spherules with and without axons. We then compared them to the retracted spherules in a disease model, mice that overexpress Dscam (Down syndrome cell adhesion molecule), to gain a better understanding of the rod synapse in health and disease. We reconstructed serial EM images of wild type and DscamGoF (gain of function) rod spherules at a resolution of 7 nm in the X-Y axis and 60 nm in the Z axis. Rod spherules with and without axons, and retracted spherules in the DscamGoF retina, were reconstructed. The rod spherule intracellular organelles, the invaginating dendrites of rod bipolar cells and horizontal cell axon tips were also reconstructed for statistical analysis. Stereotypical rod (R1) spherules occupy the outer two-thirds of the outer plexiform layer (OPL), where they present as spherical terminals with large mitochondria. This spherule group is highly uniform and composed more than 90% of the rod spherule population. Rod spherules lacking an axon (R2) were also described and characterized. This rod spherule group consists of a specific spatial organization that is strictly located at the apical OPL-facing layer of the Outer Nuclear Layer (ONL). The R2 spherule displays a large bowl-shaped synaptic terminal that hugs the rod soma. Retracted spherules in the DscamGoF retina were also reconstructed to test if they are structurally similar to R2 spherules. The misplaced rod spherules in DscamGoF have a gross morphology that is similar to R2 spherules but have significant disruption in internal synapse organization. We described a morphological diversity within Mus musculus rod spherules. This diversity is correlated with rod location in the ONL and contributes to the intracellular differences within spherules. Analysis of the DscamGoF retina indicated that their R2 spherules are not significantly different than wild type R2 spherules, but that their retracted rod spherules have abnormal synaptic organization.

The Depression Anxiety Stress Scales (DASS): normative data and latent structure in a large non-clinical sample.

PubMed

Crawford, John R; Henry, Julie D

2003-06-01

To provide UK normative data for the Depression Anxiety and Stress Scale (DASS) and test its convergent, discriminant and construct validity. Cross-sectional, correlational and confirmatory factor analysis (CFA). The DASS was administered to a non-clinical sample, broadly representative of the general adult UK population (N = 1,771) in terms of demographic variables. Competing models of the latent structure of the DASS were derived from theoretical and empirical sources and evaluated using confirmatory factor analysis. Correlational analysis was used to determine the influence of demographic variables on DASS scores. The convergent and discriminant validity of the measure was examined through correlating the measure with two other measures of depression and anxiety (the HADS and the sAD), and a measure of positive and negative affectivity (the PANAS). The best fitting model (CFI =.93) of the latent structure of the DASS consisted of three correlated factors corresponding to the depression, anxiety and stress scales with correlated error permitted between items comprising the DASS subscales. Demographic variables had only very modest influences on DASS scores. The reliability of the DASS was excellent, and the measure possessed adequate convergent and discriminant validity Conclusions: The DASS is a reliable and valid measure of the constructs it was intended to assess. The utility of this measure for UK clinicians is enhanced by the provision of large sample normative data.

Latent structure analysis of the process variables and pharmaceutical responses of an orally disintegrating tablet.

PubMed

Hayashi, Yoshihiro; Oshima, Etsuko; Maeda, Jin; Onuki, Yoshinori; Obata, Yasuko; Takayama, Kozo

2012-01-01

A multivariate statistical technique was applied to the design of an orally disintegrating tablet and to clarify the causal correlation among variables of the manufacturing process and pharmaceutical responses. Orally disintegrating tablets (ODTs) composed mainly of mannitol were prepared via the wet-granulation method using crystal transition from the δ to the β form of mannitol. Process parameters (water amounts (X(1)), kneading time (X(2)), compression force (X(3)), and amounts of magnesium stearate (X(4))) were optimized using a nonlinear response surface method (RSM) incorporating a thin plate spline interpolation (RSM-S). The results of a verification study revealed that the experimental responses, such as tensile strength and disintegration time, coincided well with the predictions. A latent structure analysis of the pharmaceutical formulations of the tablet performed using a Bayesian network led to the clear visualization of a causal connection among variables of the manufacturing process and tablet characteristics. The quantity of β-mannitol in the granules (Q(β)) was affected by X(2) and influenced all granule properties. The specific surface area of the granules was affected by X(1) and Q(β) and had an effect on all tablet characteristics. Moreover, the causal relationships among the variables were clarified by inferring conditional probability distributions. These techniques provide a better understanding of the complicated latent structure among variables of the manufacturing process and tablet characteristics.

Annealing kinetics of latent particle tracks in Durango apatite

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

Afra, B.; Rodriguez, M. D.; Giulian, R.

2011-02-01

Using synchrotron small-angle x-ray scattering we determine the ''latent'' track morphology and the track annealing kinetics in the Durango apatite. The latter, measured during ex situ and in situ annealing experiments, suggests structural relaxation followed by recrystallization of the damaged material. The resolution of fractions of a nanometer with which the track radii are determined, as well as the nondestructive, artefact-free measurement methodology shown here, provides an effective means for in-depth studies of ion-track formation in natural minerals under a wide variety of geological conditions.

Maximum Likelihood Analysis of a Two-Level Nonlinear Structural Equation Model with Fixed Covariates

ERIC Educational Resources Information Center

Lee, Sik-Yum; Song, Xin-Yuan

2005-01-01

In this article, a maximum likelihood (ML) approach for analyzing a rather general two-level structural equation model is developed for hierarchically structured data that are very common in educational and/or behavioral research. The proposed two-level model can accommodate nonlinear causal relations among latent variables as well as effects…

A Maximum Likelihood Approach for Multisample Nonlinear Structural Equation Models with Missing Continuous and Dichotomous Data

ERIC Educational Resources Information Center

Song, Xin-Yuan; Lee, Sik-Yum

2006-01-01

Structural equation models are widely appreciated in social-psychological research and other behavioral research to model relations between latent constructs and manifest variables and to control for measurement error. Most applications of SEMs are based on fully observed continuous normal data and models with a linear structural equation.…

Impact of Diagnosticity on the Adequacy of Models for Cognitive Diagnosis under a Linear Attribute Structure: A Simulation Study

ERIC Educational Resources Information Center

de La Torre, Jimmy; Karelitz, Tzur M.

2009-01-01

Compared to unidimensional item response models (IRMs), cognitive diagnostic models (CDMs) based on latent classes represent examinees' knowledge and item requirements using discrete structures. This study systematically examines the viability of retrofitting CDMs to IRM-based data with a linear attribute structure. The study utilizes a procedure…

Detailed partial load investigation of a thermal energy storage concept for solar thermal power plants with direct steam generation

NASA Astrophysics Data System (ADS)

Seitz, M.; Hübner, S.; Johnson, M.

2016-05-01

Direct steam generation enables the implementation of a higher steam temperature for parabolic trough concentrated solar power plants. This leads to much better cycle efficiencies and lower electricity generating costs. For a flexible and more economic operation of such a power plant, it is necessary to develop thermal energy storage systems for the extension of the production time of the power plant. In the case of steam as the heat transfer fluid, it is important to use a storage material that uses latent heat for the storage process. This leads to a minimum of exergy losses during the storage process. In the case of a concentrating solar power plant, superheated steam is needed during the discharging process. This steam cannot be superheated by the latent heat storage system. Therefore, a sensible molten salt storage system is used for this task. In contrast to the state-of-the-art thermal energy storages within the concentrating solar power area of application, a storage system for a direct steam generation plant consists of a latent and a sensible storage part. Thus far, no partial load behaviors of sensible and latent heat storage systems have been analyzed in detail. In this work, an optimized fin structure was developed in order to minimize the costs of the latent heat storage. A complete system simulation of the power plant process, including the solar field, power block and sensible and latent heat energy storage calculates the interaction between the solar field, the power block and the thermal energy storage system.

Optical Power Limiting Liquid Crystal Composites

DTIC Science & Technology

1994-11-10

essentially a measurement of self -focusing by the sample; the nonlinear refractive index of the sample can be readily determined from intensity of the...transmitted ligse is detected th e tw o trasmted eetofteirtpulses have he the samst respose regardlessd, the sapeostnrltieton thle f"creints This implies that...these materials on the nanosecond time regime has also been observed. In Fig. 19 we show the OPL respose of a 25 pm thick sample of i nematic 5CB

NDI Acquisition. An Alternative to Business as Usual. Report of the DSMC 1991-1992 Military Research Fellows

DTIC Science & Technology

1992-10-01

sealed bidding and competitive proposals. governed by the same regulations and laws The sealed bidding procedure requires ade- that govern procurement ...Summary xiv NDI ACQUISITION: An Alternative to "Business as Usual" to successful, effective government procure - posal Cover Sheet). Moreover, the...became policy when the OPlP ;,;sued the first opment costs. These benefits may be offset by in a series of memoranda governing procure - performance

Metabolic Profiling in Patients with Pneumonia on Intensive Care.

PubMed

Antcliffe, David; Jiménez, Beatriz; Veselkov, Kirill; Holmes, Elaine; Gordon, Anthony C

2017-04-01

Clinical features and investigations lack predictive value when diagnosing pneumonia, especially when patients are ventilated and when patients develop ventilator associated pneumonia (VAP). New tools to aid diagnosis are important to improve outcomes. This pilot study examines the potential for metabolic profiling to aid the diagnosis in critical care. In this prospective observational study ventilated patients with brain injuries or pneumonia were recruited in the intensive care unit and serum samples were collected soon after the start of ventilation. Metabolic profiles were produced using 1D 1 H NMR spectra. Metabolic data were compared using multivariate statistical techniques including Principal Component Analysis (PCA) and Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA). We recruited 15 patients with pneumonia and 26 with brain injuries, seven of whom went on to develop VAP. Comparison of metabolic profiles using OPLS-DA differentiated those with pneumonia from those with brain injuries (R 2 Y=0.91, Q 2 Y=0.28, p=0.02) and those with VAP from those without (R 2 Y=0.94, Q 2 Y=0.27, p=0.05). Metabolites that differentiated patients with pneumonia included lipid species, amino acids and glycoproteins. Metabolic profiling shows promise to aid in the diagnosis of pneumonia in ventilated patients and may allow a more timely diagnosis and better use of antibiotics. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

UHPLC-Q-Orbitrap-HRMS-based global metabolomics reveal metabolome modifications in plasma of young women after cranberry juice consumption.

PubMed

Liu, Haiyan; Garrett, Timothy J; Su, Zhihua; Khoo, Christina; Gu, Liwei

2017-07-01

Plasma metabolome in young women following cranberry juice consumption were investigated using a global UHPLC-Q-Orbitrap-HRMS approach. Seventeen female college students, between 21 and 29 years old, were given either cranberry juice or apple juice for three days using a cross-over design. Plasma samples were collected before and after juice consumption. Plasma metabolomes were analyzed using UHPLC-Q-Orbitrap-HRMS followed by orthogonal partial least squares-discriminant analyses (OPLS-DA). S-plot was used to identify discriminant metabolites. Validated OPLS-DA analyses showed that the plasma metabolome in young women, including both exogenous and endogenous metabolites, were altered following cranberry juice consumption. Cranberry juice caused increases of exogenous metabolites including quinic acid, vanilloloside, catechol sulfate, 3,4-dihydroxyphenyl ethanol sulfate, coumaric acid sulfate, ferulic acid sulfate, 5-(trihydroxphenyl)-gamma-valerolactone, 3-(hydroxyphenyl)proponic acid, hydroxyphenylacetic acid and trihydroxybenzoic acid. In addition, the plasma levels of endogenous metabolites including citramalic acid, aconitic acid, hydroxyoctadecanoic acid, hippuric acid, 2-hydroxyhippuric acid, vanilloylglycine, 4-acetamido-2-aminobutanoic acid, dihydroxyquinoline, and glycerol 3-phosphate were increased in women following cranberry juice consumption. The metabolic differences and discriminant metabolites observed in this study may serve as biomarkers of cranberry juice consumption and explain its health promoting properties in human. Copyright © 2017 Elsevier Inc. All rights reserved.

Evaluation of genetic variability in micropropagated propagules of ornamental pineapple [Ananas comosus var. bracteatus (Lindley) Coppens and Leal] using RAPD markers.

PubMed

Santos, M D M; Buso, G C S; Torres, A C

2008-10-21

The objective of the present study was to evaluate the genetic variability in micropropagated plantlets of ornamental pineapple, after the fourth period of subculture. The basal culture medium consisted of MS salts, vitamins, 3% sucrose, liquid formulation, supplemented with 6-benzylaminopurine (BAP) at concentrations of 0.125, 0.25, 0.5, 1.0, and 2.0 mg/L. The addition of BAP influenced the occurrence of genetic variation revealed using random amplified polymorphic DNA (RAPD) markers. Of a total of 520 primers tested, 44 were selected and amplified; 402 monomorphic bands (97.2%) and 18 polymorphic bands (2.8%) resulted among regenerated plantlets. The polymorphic fragments were produced by 12 primers (OPA-01, OPA-20, OPB-01, OPB-19, OPC-19, OPF-13, OPL-17, OPM-13, OPP-16, OPT-07, OPV-19, and OPX-03). Among the primers that identified polymorphism, OPA-01, OPA-20, OPB-19, OPC-19, OPL-17, OPP-16, and OPX-3 each showed, one polymorphic band and OPF-13 amplified a maximum of three bands. In this study, the RAPD technique was effective in showing the occurrence of somaclonal variations that occur during the micropropagation process of ornamental pineapple cultivation in BAP-supplemented medium, and it is possible to detect the presence of genetic variation in early stages of plant development.

[Discriminant Analysis of Lavender Essential Oil by Attenuated Total Reflectance Infrared Spectroscopy].

PubMed

Tang, Jun; Wang, Qing; Tong, Hong; Liao, Xiang; Zhang, Zheng-fang

2016-03-01

This work aimed to use attenuated total reflectance Fourier transform infrared spectroscopy to identify the lavender essential oil by establishing a Lavender variety and quality analysis model. So, 96 samples were tested. For all samples, the raw spectra were pretreated as second derivative, and to determine the 1 750-900 cm(-1) wavelengths for pattern recognition analysis on the basis of the variance calculation. The results showed that principal component analysis (PCA) can basically discriminate lavender oil cultivar and the first three principal components mainly represent the ester, alcohol and terpenoid substances. When the orthogonal partial least-squares discriminant analysis (OPLS-DA) model was established, the 68 samples were used for the calibration set. Determination coefficients of OPLS-DA regression curve were 0.959 2, 0.976 4, and 0.958 8 respectively for three varieties of lavender essential oil. Three varieties of essential oil's the root mean square error of prediction (RMSEP) in validation set were 0.142 9, 0.127 3, and 0.124 9, respectively. The discriminant rate of calibration set and the prediction rate of validation set had reached 100%. The model has the very good recognition capability to detect the variety and quality of lavender essential oil. The result indicated that a model which provides a quick, intuitive and feasible method had been built to discriminate lavender oils.

Rasch Mixture Models for DIF Detection

PubMed Central

Strobl, Carolin; Zeileis, Achim

2014-01-01

Rasch mixture models can be a useful tool when checking the assumption of measurement invariance for a single Rasch model. They provide advantages compared to manifest differential item functioning (DIF) tests when the DIF groups are only weakly correlated with the manifest covariates available. Unlike in single Rasch models, estimation of Rasch mixture models is sensitive to the specification of the ability distribution even when the conditional maximum likelihood approach is used. It is demonstrated in a simulation study how differences in ability can influence the latent classes of a Rasch mixture model. If the aim is only DIF detection, it is not of interest to uncover such ability differences as one is only interested in a latent group structure regarding the item difficulties. To avoid any confounding effect of ability differences (or impact), a new score distribution for the Rasch mixture model is introduced here. It ensures the estimation of the Rasch mixture model to be independent of the ability distribution and thus restricts the mixture to be sensitive to latent structure in the item difficulties only. Its usefulness is demonstrated in a simulation study, and its application is illustrated in a study of verbal aggression. PMID:29795819

Causal mediation analysis with a latent mediator.

PubMed

Albert, Jeffrey M; Geng, Cuiyu; Nelson, Suchitra

2016-05-01

Health researchers are often interested in assessing the direct effect of a treatment or exposure on an outcome variable, as well as its indirect (or mediation) effect through an intermediate variable (or mediator). For an outcome following a nonlinear model, the mediation formula may be used to estimate causally interpretable mediation effects. This method, like others, assumes that the mediator is observed. However, as is common in structural equations modeling, we may wish to consider a latent (unobserved) mediator. We follow a potential outcomes framework and assume a generalized structural equations model (GSEM). We provide maximum-likelihood estimation of GSEM parameters using an approximate Monte Carlo EM algorithm, coupled with a mediation formula approach to estimate natural direct and indirect effects. The method relies on an untestable sequential ignorability assumption; we assess robustness to this assumption by adapting a recently proposed method for sensitivity analysis. Simulation studies show good properties of the proposed estimators in plausible scenarios. Our method is applied to a study of the effect of mother education on occurrence of adolescent dental caries, in which we examine possible mediation through latent oral health behavior. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A unified genetic association test robust to latent population structure for a count phenotype.

PubMed

Song, Minsun

2018-06-04

Confounding caused by latent population structure in genome-wide association studies has been a big concern despite the success of genome-wide association studies at identifying genetic variants associated with complex diseases. In particular, because of the growing interest in association mapping using count phenotype data, it would be interesting to develop a testing framework for genetic associations that is immune to population structure when phenotype data consist of count measurements. Here, I propose a solution for testing associations between single nucleotide polymorphisms and a count phenotype in the presence of an arbitrary population structure. I consider a classical range of models for count phenotype data. Under these models, a unified test for genetic associations that protects against confounding was derived. An algorithm was developed to efficiently estimate the parameters that are required to fit the proposed model. I illustrate the proposed approach using simulation studies and an empirical study. Both simulated and real-data examples suggest that the proposed method successfully corrects population structure. Copyright © 2018 John Wiley & Sons, Ltd.

Development of Drugs for Epstein - Barr virus using High-Throughput in silico Virtual Screening

PubMed Central

Li, Ning; Thompson, Scott; Jiang, Hualiang; Lieberman, Paul M.; Luo, Cheng

2010-01-01

Importance of the field Epstein-Barr virus (EBV) is a ubiquitious human herpesvirus that is causally associated with endemic forms of Burkitt’s lymphoma (BL), nasopharyngeal carcinoma, and lymphoproliferative disease in immunosuppressed individuals. On a global scale, EBV infects over 90% of the adult population and is responsible for ~1% of all human cancers. To date, there is no efficacious drug or therapy for the treatment of EBV infection and EBV-related diseases. Areas covered in this review In this review, we discuss the existing anti-EBV inhibitors and those under development. We discuss the value of different molecular targets, including EBV lytic DNA replication enzymes, as well as proteins that are expressed exclusively during latent infection, like EBNA1 and LMP1. Since the atomic structure of the EBNA1 DNA binding domain has been described, it is an attractive target for in silico methods of drug design and small molecule screening. We discuss the use of computational methods that can greatly facilitate the development of novel inhibitors and how in silico screening methods can be applied to target proteins with known structures, like EBNA1, to treat EBV infection and disease. What the reader will gain The reader will be familiarized with the problems in targeting of EBV for inhibition by small molecules and how computational methods can greatly facilitate this process. Take home message Despite the impressive efficacy of nucleoside analogues for the treatment of herpesvirus lytic infection, there remain few effective treatments for latent infections. Since EBV-latent infection persists within and contributes to the formation of EBV-associated cancers, targeting EBV latent proteins is an unmet medical need. High throughput in silico screening can accelerate the process of drug discovery for novel and selective agents that inhibit EBV latent infection and associated disease. PMID:22822721

TENSOR DECOMPOSITIONS AND SPARSE LOG-LINEAR MODELS

PubMed Central

Johndrow, James E.; Bhattacharya, Anirban; Dunson, David B.

2017-01-01

Contingency table analysis routinely relies on log-linear models, with latent structure analysis providing a common alternative. Latent structure models lead to a reduced rank tensor factorization of the probability mass function for multivariate categorical data, while log-linear models achieve dimensionality reduction through sparsity. Little is known about the relationship between these notions of dimensionality reduction in the two paradigms. We derive several results relating the support of a log-linear model to nonnegative ranks of the associated probability tensor. Motivated by these findings, we propose a new collapsed Tucker class of tensor decompositions, which bridge existing PARAFAC and Tucker decompositions, providing a more flexible framework for parsimoniously characterizing multivariate categorical data. Taking a Bayesian approach to inference, we illustrate empirical advantages of the new decompositions. PMID:29332971

CORRECTING FOR MEASUREMENT ERROR IN LATENT VARIABLES USED AS PREDICTORS*

PubMed Central

Schofield, Lynne Steuerle

2015-01-01

This paper represents a methodological-substantive synergy. A new model, the Mixed Effects Structural Equations (MESE) model which combines structural equations modeling and item response theory is introduced to attend to measurement error bias when using several latent variables as predictors in generalized linear models. The paper investigates racial and gender disparities in STEM retention in higher education. Using the MESE model with 1997 National Longitudinal Survey of Youth data, I find prior mathematics proficiency and personality have been previously underestimated in the STEM retention literature. Pre-college mathematics proficiency and personality explain large portions of the racial and gender gaps. The findings have implications for those who design interventions aimed at increasing the rates of STEM persistence among women and under-represented minorities. PMID:26977218