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Sample records for quantitative structure-retention relationships

Quantitative structure-retention relationships for gas chromatographic retention indices of alkylbenzenes with molecular graph descriptors.

PubMed

Ivanciuc, O; Ivanciuc, T; Klein, D J; Seitz, W A; Balaban, A T

2001-02-01

Quantitative structure-retention relationships (QSRR) represent statistical models that quantify the connection between the molecular structure and the chromatographic retention indices of organic compounds, allowing the prediction of retention indices of novel, not yet synthesized compounds, solely from their structural descriptors. Using multiple linear regression, QSRR models for the gas chromatographic Kováts retention indices of 129 alkylbenzenes are generated using molecular graph descriptors. The correlational ability of structural descriptors computed from 10 molecular matrices is investigated, showing that the novel reciprocal matrices give numerical indices with improved correlational ability. A QSRR equation with 5 graph descriptors gives the best calibration and prediction results, demonstrating the usefulness of the molecular graph descriptors in modeling chromatographic retention parameters. The sequential orthogonalization of descriptors suggests simpler QSRR models by eliminating redundant structural information.
[Quantitative relationship between gas chromatographic retention time and structural parameters of alkylphenols].

PubMed

Ruan, Xiaofang; Zhang, Ruisheng; Yao, Xiaojun; Liu, Mancang; Fan, Botao

2007-03-01

Alkylphenols are a group of permanent pollutants in the environment and could adversely disturb the human endocrine system. It is therefore important to effectively separate and measure the alkylphenols. To guide the chromatographic analysis of these compounds in practice, the development of quantitative relationship between the molecular structure and the retention time of alkylphenols becomes necessary. In this study, topological, constitutional, geometrical, electrostatic and quantum-chemical descriptors of 44 alkylphenols were calculated using a software, CODESSA, and these descriptors were pre-selected using the heuristic method. As a result, three-descriptor linear model (LM) was developed to describe the relationship between the molecular structure and the retention time of alkylphenols. Meanwhile, the non-linear regression model was also developed based on support vector machine (SVM) using the same three descriptors. The correlation coefficient (R(2)) for the LM and SVM was 0.98 and 0. 92, and the corresponding root-mean-square error was 0. 99 and 2. 77, respectively. By comparing the stability and prediction ability of the two models, it was found that the linear model was a better method for describing the quantitative relationship between the retention time of alkylphenols and the molecular structure. The results obtained suggested that the linear model could be applied for the chromatographic analysis of alkylphenols with known molecular structural parameters.
Quantitative structure-retention relationships of polycyclic aromatic hydrocarbons gas-chromatographic retention indices.

PubMed

Drosos, Juan Carlos; Viola-Rhenals, Maricela; Vivas-Reyes, Ricardo

2010-06-25

Polycyclic aromatic compounds (PAHs) are of concern in environmental chemistry and toxicology. In the present work, a QSRR study was performed for 209 previously reported PAHs using quantum mechanics and other sources descriptors estimated by different approaches. The B3LYP/6-31G* level of theory was used for geometrical optimization and quantum mechanics related variables. A good linear relationship between gas-chromatographic retention index and electronic or topologic descriptors was found by stepwise linear regression analysis. The molecular polarizability (alpha) and the second order molecular connectivity Kier and Hall index ((2)chi) showed evidence of significant correlation with retention index by means of important squared coefficient of determination, (R(2)), values (R(2)=0.950 and 0.962, respectively). A one variable QSRR model is presented for each descriptor and both models demonstrates a significant predictive capacity established using the leave-many-out LMO (excluding 25% of rows) cross validation method's q(2) cross-validation coefficients q(2)(CV-LMO25%), (obtained q(2)(CV-LMO25%) 0.947 and 0.960, respectively). Furthermore, the physicochemical interpretation of selected descriptors allowed detailed explanation of the source of the observed statistical correlation. The model analysis suggests that only one descriptor is sufficient to establish a consistent retention index-structure relationship. Moderate or non-significant improve was observed for quantitative results or statistical validation parameters when introducing more terms in predictive equation. The one parameter QSRR proposed model offers a consistent scheme to predict chromatographic properties of PAHs compounds. Copyright 2010 Elsevier B.V. All rights reserved.
Quantitative structure-retention relationships of flavonoids unraveled by immobilized artificial membrane chromatography.

PubMed

Santoro, Adriana Leandra; Carrilho, Emanuel; Lanças, Fernando Mauro; Montanari, Carlos Alberto

2016-06-10

The pharmacokinetic properties of flavonoids with differing degrees of lipophilicity were investigated using immobilized artificial membranes (IAMs) as the stationary phase in high performance liquid chromatography (HPLC). For each flavonoid compound, we investigated whether the type of column used affected the correlation between the retention factors and the calculated octanol/water partition (log Poct). Three-dimensional (3D) molecular descriptors were calculated from the molecular structure of each compound using i) VolSurf software, ii) the GRID method (computational procedure for determining energetically favorable binding sites in molecules of known structure using a probe for calculating the 3D molecular interaction fields, between the probe and the molecule), and iii) the relationship between partition and molecular structure, analyzed in terms of physicochemical descriptors. The VolSurf built-in Caco-2 model was used to estimate compound permeability. The extent to which the datasets obtained from different columns differ both from each other and from both the calculated log Poct and the predicted permeability in Caco-2 cells was examined by principal component analysis (PCA). The immobilized membrane partition coefficients (kIAM) were analyzed using molecular descriptors in partial least square regression (PLS) and a quantitative structure-retention relationship was generated for the chromatographic retention in the cholesterol column. The cholesterol column provided the best correlation with the permeability predicted by the Caco-2 cell model and a good fit model with great prediction power was obtained for its retention data (R(2)=0.96 and Q(2)=0.85 with four latent variables). Copyright © 2015 Elsevier B.V. All rights reserved.
Genetic programming based quantitative structure-retention relationships for the prediction of Kovats retention indices.

PubMed

Goel, Purva; Bapat, Sanket; Vyas, Renu; Tambe, Amruta; Tambe, Sanjeev S

2015-11-13

The development of quantitative structure-retention relationships (QSRR) aims at constructing an appropriate linear/nonlinear model for the prediction of the retention behavior (such as Kovats retention index) of a solute on a chromatographic column. Commonly, multi-linear regression and artificial neural networks are used in the QSRR development in the gas chromatography (GC). In this study, an artificial intelligence based data-driven modeling formalism, namely genetic programming (GP), has been introduced for the development of quantitative structure based models predicting Kovats retention indices (KRI). The novelty of the GP formalism is that given an example dataset, it searches and optimizes both the form (structure) and the parameters of an appropriate linear/nonlinear data-fitting model. Thus, it is not necessary to pre-specify the form of the data-fitting model in the GP-based modeling. These models are also less complex, simple to understand, and easy to deploy. The effectiveness of GP in constructing QSRRs has been demonstrated by developing models predicting KRIs of light hydrocarbons (case study-I) and adamantane derivatives (case study-II). In each case study, two-, three- and four-descriptor models have been developed using the KRI data available in the literature. The results of these studies clearly indicate that the GP-based models possess an excellent KRI prediction accuracy and generalization capability. Specifically, the best performing four-descriptor models in both the case studies have yielded high (>0.9) values of the coefficient of determination (R(2)) and low values of root mean squared error (RMSE) and mean absolute percent error (MAPE) for training, test and validation set data. The characteristic feature of this study is that it introduces a practical and an effective GP-based method for developing QSRRs in gas chromatography that can be gainfully utilized for developing other types of data-driven models in chromatography science
[Quantitative structure-gas chromatographic retention relationship of polycyclic aromatic sulfur heterocycles using molecular electronegativity-distance vector].

PubMed

Li, Zhenghua; Cheng, Fansheng; Xia, Zhining

2011-01-01

The chemical structures of 114 polycyclic aromatic sulfur heterocycles (PASHs) have been studied by molecular electronegativity-distance vector (MEDV). The linear relationships between gas chromatographic retention index and the MEDV have been established by a multiple linear regression (MLR) model. The results of variable selection by stepwise multiple regression (SMR) and the powerful predictive abilities of the optimization model appraised by leave-one-out cross-validation showed that the optimization model with the correlation coefficient (R) of 0.994 7 and the cross-validated correlation coefficient (Rcv) of 0.994 0 possessed the best statistical quality. Furthermore, when the 114 PASHs compounds were divided into calibration and test sets in the ratio of 2:1, the statistical analysis showed our models possesses almost equal statistical quality, the very similar regression coefficients and the good robustness. The quantitative structure-retention relationship (QSRR) model established may provide a convenient and powerful method for predicting the gas chromatographic retention of PASHs.
Quantitative structure-retention relationship studies using immobilized artificial membrane chromatography I: amended linear solvation energy relationships with the introduction of a molecular electronic factor.

PubMed

Li, Jie; Sun, Jin; Cui, Shengmiao; He, Zhonggui

2006-11-03

Linear solvation energy relationships (LSERs) amended by the introduction of a molecular electronic factor were employed to establish quantitative structure-retention relationships using immobilized artificial membrane (IAM) chromatography, in particular ionizable solutes. The chromatographic indices, log k(IAM), were determined by HPLC on an IAM.PC.DD2 column for 53 structurally diverse compounds, including neutral, acidic and basic compounds. Unlike neutral compounds, the IAM chromatographic retention of ionizable compounds was affected by their molecular charge state. When the mean net charge per molecule (delta) was introduced into the amended LSER as the sixth variable, the LSER regression coefficient was significantly improved for the test set including ionizable solutes. The delta coefficients of acidic and basic compounds were quite different indicating that the molecular electronic factor had a markedly different impact on the retention of acidic and basic compounds on IAM column. Ionization of acidic compounds containing a carboxylic group tended to impair their retention on IAM, while the ionization of basic compounds did not have such a marked effect. In addition, the extra-interaction with the polar head of phospholipids might cause a certain change in the retention of basic compounds. A comparison of calculated and experimental retention indices suggested that the semi-empirical LSER amended by the addition of a molecular electronic factor was able to reproduce adequately the experimental retention factors of the structurally diverse solutes investigated.
Predicting Retention Times of Naturally Occurring Phenolic Compounds in Reversed-Phase Liquid Chromatography: A Quantitative Structure-Retention Relationship (QSRR) Approach

PubMed Central

Akbar, Jamshed; Iqbal, Shahid; Batool, Fozia; Karim, Abdul; Chan, Kim Wei

2012-01-01

Quantitative structure-retention relationships (QSRRs) have successfully been developed for naturally occurring phenolic compounds in a reversed-phase liquid chromatographic (RPLC) system. A total of 1519 descriptors were calculated from the optimized structures of the molecules using MOPAC2009 and DRAGON softwares. The data set of 39 molecules was divided into training and external validation sets. For feature selection and mapping we used step-wise multiple linear regression (SMLR), unsupervised forward selection followed by step-wise multiple linear regression (UFS-SMLR) and artificial neural networks (ANN). Stable and robust models with significant predictive abilities in terms of validation statistics were obtained with negation of any chance correlation. ANN models were found better than remaining two approaches. HNar, IDM, Mp, GATS2v, DISP and 3D-MoRSE (signals 22, 28 and 32) descriptors based on van der Waals volume, electronegativity, mass and polarizability, at atomic level, were found to have significant effects on the retention times. The possible implications of these descriptors in RPLC have been discussed. All the models are proven to be quite able to predict the retention times of phenolic compounds and have shown remarkable validation, robustness, stability and predictive performance. PMID:23203132
Quantitative structure-retention relationship models for the prediction of the reversed-phase HPLC gradient retention based on the heuristic method and support vector machine.

PubMed

Du, Hongying; Wang, Jie; Yao, Xiaojun; Hu, Zhide

2009-01-01

The heuristic method (HM) and support vector machine (SVM) were used to construct quantitative structure-retention relationship models by a series of compounds to predict the gradient retention times of reversed-phase high-performance liquid chromatography (HPLC) in three different columns. The aims of this investigation were to predict the retention times of multifarious compounds, to find the main properties of the three columns, and to indicate the theory of separation procedures. In our method, we correlated the retention times of many diverse structural analytes in three columns (Symmetry C18, Chromolith, and SG-MIX) with their representative molecular descriptors, calculated from the molecular structures alone. HM was used to select the most important molecular descriptors and build linear regression models. Furthermore, non-linear regression models were built using the SVM method; the performance of the SVM models were better than that of the HM models, and the prediction results were in good agreement with the experimental values. This paper could give some insights into the factors that were likely to govern the gradient retention process of the three investigated HPLC columns, which could theoretically supervise the practical experiment.
Quantitative structure-retention relationship studies with immobilized artificial membrane chromatography II: partial least squares regression.

PubMed

Li, Jie; Sun, Jin; He, Zhonggui

2007-01-26

We aimed to establish quantitative structure-retention relationship (QSRR) with immobilized artificial membrane (IAM) chromatography using easily understood and obtained physicochemical molecular descriptors and to elucidate which descriptors are critical to affect the interaction process between solutes and immobilized phospholipid membranes. The retention indices (logk(IAM)) of 55 structurally diverse drugs were determined on an immobilized artificial membrane column (IAM.PC.DD2) directly or obtained by extrapolation method for highly hydrophobic compounds. Ten simple physicochemical property descriptors (clogP, rings, rotatory bond, hydro-bond counting, etc.) of these drugs were collected and used to establish QSRR and predict the retention data by partial least squares regression (PLSR). Five descriptors, clogP, rotatory bond (RotB), rings, molecular weight (MW) and total surface area (TSA), were reserved by using the Variable Importance for Projection (VIP) values as criterion to build the final PLSR model. An external test set was employed to verify the QSRR based on the training set with the five variables, and QSRR by PLSR exhibited a satisfying predictive ability with R(p)=0.902 and RMSE(p)=0.400. Comparison of coefficients of centered and scaled variables by PLSR demonstrated that, for the descriptors studied, clogP and TSA have the most significant positive effect but the rotatable bond has significant negative effect on drug IAM chromatographic retention.
Quantitative structure-retention relationship studies for taxanes including epimers and isomeric metabolites in ultra fast liquid chromatography.

PubMed

Dong, Pei-Pei; Ge, Guang-Bo; Zhang, Yan-Yan; Ai, Chun-Zhi; Li, Guo-Hui; Zhu, Liang-Liang; Luan, Hong-Wei; Liu, Xing-Bao; Yang, Ling

2009-10-16

Seven pairs of epimers and one pair of isomeric metabolites of taxanes, each pair of which have similar structures but different retention behaviors, together with additional 13 taxanes with different substitutions were chosen to investigate the quantitative structure-retention relationship (QSRR) of taxanes in ultra fast liquid chromatography (UFLC). Monte Carlo variable selection (MCVS) method was adopted to choose descriptors. The selected four descriptors were used to build QSRR model with multi-linear regression (MLR) and artificial neural network (ANN) modeling techniques. Both linear and nonlinear models show good predictive ability, of which ANN model was better with the determination coefficient R(2) for training, validation and test set being 0.9892, 0.9747 and 0.9840, respectively. The results of 100 times' leave-12-out cross validation showed the robustness of this model. All the isomers can be correctly differentiated by this model. According to the selected descriptors, the three dimensional structural information was critical for recognition of epimers. Hydrophobic interaction was the uppermost factor for retention in UFLC. Molecules' polarizability and polarity properties were also closely correlated with retention behaviors. This QSRR model will be useful for separation and identification of taxanes including epimers and metabolites from botanical or biological samples.
Application of the artificial neural network in quantitative structure-gradient elution retention relationship of phenylthiocarbamyl amino acids derivatives.

PubMed

Tham, S Y; Agatonovic-Kustrin, S

2002-05-15

Quantitative structure-retention relationship(QSRR) method was used to model reversed-phase high-performance liquid chromatography (RP-HPLC) separation of 18 selected amino acids. Retention data for phenylthiocarbamyl (PTC) amino acids derivatives were obtained using gradient elution on ODS column with mobile phase of varying acetonitrile, acetate buffer and containing 0.5 ml/l of triethylamine (TEA). Molecular structure of each amino acid was encoded with 36 calculated molecular descriptors. The correlation between the molecular descriptors and the retention time of the compounds in the calibration set was established using the genetic neural network method. A genetic algorithm (GA) was used to select important molecular descriptors and supervised artificial neural network (ANN) was used to correlate mobile phase composition and selected descriptors with the experimentally derived retention times. Retention time values were used as the network's output and calculated molecular descriptors and mobile phase composition as the inputs. The best model with five input descriptors was chosen, and the significance of the selected descriptors for amino acid separation was examined. Results confirmed the dominant role of the organic modifier in such chromatographic systems in addition to lipophilicity (log P) and molecular size and shape (topological indices) of investigated solutes.
Mass Spectrometry Based Identification of Geometric Isomers during Metabolic Stability Study of a New Cytotoxic Sulfonamide Derivatives Supported by Quantitative Structure-Retention Relationships

PubMed Central

Belka, Mariusz; Hewelt-Belka, Weronika; Sławiński, Jarosław; Bączek, Tomasz

2014-01-01

A set of 15 new sulphonamide derivatives, presenting antitumor activity have been subjected to a metabolic stability study. The results showed that besides products of biotransformation, some additional peaks occurred in chromatograms. Tandem mass spectrometry revealed the same mass and fragmentation pathway, suggesting that geometric isomerization occurred. Thus, to support this hypothesis, quantitative structure-retention relationships were applied. Human liver microsomes were used as an in vitro model of metabolism. The biotransformation reactions were tracked by liquid chromatography assay and additionally, fragmentation mass spectra were recorded. In silico molecular modeling at a semi-empirical level was conducted as a starting point for molecular descriptor calculations. A quantitative structure-retention relationship model was built applying multiple linear regression based on selected three-dimensional descriptors. The studied compounds revealed high metabolic stability, with a tendency to form hydroxylated biotransformation products. However, significant chemical instability in conditions simulating human body fluids was noticed. According to literature and MS data geometrical isomerization was suggested. The developed in sillico model was able to describe the relationship between the geometry of isomer pairs and their chromatographic retention properties, thus it supported the hypothesis that the observed pairs of peaks are most likely geometric isomers. However, extensive structural investigations are needed to fully identify isomers’ geometry. An effort to describe MS fragmentation pathways of novel chemical structures is often not enough to propose structures of potent metabolites and products of other chemical reactions that can be observed in compound solutions at early drug discovery studies. The results indicate that the relatively non-expensive and not time- and labor-consuming in sillico approach could be a good supportive tool assisting the
Towards a chromatographic similarity index to establish localised quantitative structure-retention relationships for retention prediction. II Use of Tanimoto similarity index in ion chromatography.

PubMed

Park, Soo Hyun; Talebi, Mohammad; Amos, Ruth I J; Tyteca, Eva; Haddad, Paul R; Szucs, Roman; Pohl, Christopher A; Dolan, John W

2017-11-10

Quantitative Structure-Retention Relationships (QSRR) are used to predict retention times of compounds based only on their chemical structures encoded by molecular descriptors. The main concern in QSRR modelling is to build models with high predictive power, allowing reliable retention prediction for the unknown compounds across the chromatographic space. With the aim of enhancing the prediction power of the models, in this work, our previously proposed QSRR modelling approach called "federation of local models" is extended in ion chromatography to predict retention times of unknown ions, where a local model for each target ion (unknown) is created using only structurally similar ions from the dataset. A Tanimoto similarity (TS) score was utilised as a measure of structural similarity and training sets were developed by including ions that were similar to the target ion, as defined by a threshold value. The prediction of retention parameters (a- and b-values) in the linear solvent strength (LSS) model in ion chromatography, log k=a - blog[eluent], allows the prediction of retention times under all eluent concentrations. The QSRR models for a- and b-values were developed by a genetic algorithm-partial least squares method using the retention data of inorganic and small organic anions and larger organic cations (molecular mass up to 507) on four Thermo Fisher Scientific columns (AS20, AS19, AS11HC and CS17). The corresponding predicted retention times were calculated by fitting the predicted a- and b-values of the models into the LSS model equation. The predicted retention times were also plotted against the experimental values to evaluate the goodness of fit and the predictive power of the models. The application of a TS threshold of 0.6 was found to successfully produce predictive and reliable QSRR models (Q ext(F2) 2 >0.8 and Mean Absolute Error<0.1), and hence accurate retention time predictions with an average Mean Absolute Error of 0.2min. Crown Copyright �
Quantitative structure-property relationship analysis for the retention index of fragrance-like compounds on a polar stationary phase.

PubMed

Rojas, Cristian; Duchowicz, Pablo R; Tripaldi, Piercosimo; Pis Diez, Reinaldo

2015-11-27

A quantitative structure-property relationship (QSPR) was developed for modeling the retention index of 1184 flavor and fragrance compounds measured using a Carbowax 20M glass capillary gas chromatography column. The 4885 molecular descriptors were calculated using Dragon software, and then were simultaneously analyzed through multivariable linear regression analysis using the replacement method (RM) variable subset selection technique. We proceeded in three steps, the first one by considering all descriptor blocks, the second one by excluding conformational descriptor blocks, and the last one by analyzing only 3D-descriptor families. The models were validated through an external test set of compounds. Cross-validation methods such as leave-one-out and leave-many-out were applied, together with Y-randomization and applicability domain analysis. The developed model was used to estimate the I of a set of 22 molecules. The results clearly suggest that 3D-descriptors do not offer relevant information for modeling the retention index, while a topological index such as the Randić-like index from reciprocal squared distance matrix has a high relevance for this purpose. Copyright © 2015 Elsevier B.V. All rights reserved.
Rapid Method Development in Hydrophilic Interaction Liquid Chromatography for Pharmaceutical Analysis Using a Combination of Quantitative Structure-Retention Relationships and Design of Experiments.

PubMed

Taraji, Maryam; Haddad, Paul R; Amos, Ruth I J; Talebi, Mohammad; Szucs, Roman; Dolan, John W; Pohl, Chris A

2017-02-07

A design-of-experiment (DoE) model was developed, able to describe the retention times of a mixture of pharmaceutical compounds in hydrophilic interaction liquid chromatography (HILIC) under all possible combinations of acetonitrile content, salt concentration, and mobile-phase pH with R 2 > 0.95. Further, a quantitative structure-retention relationship (QSRR) model was developed to predict retention times for new analytes, based only on their chemical structures, with a root-mean-square error of prediction (RMSEP) as low as 0.81%. A compound classification based on the concept of similarity was applied prior to QSRR modeling. Finally, we utilized a combined QSRR-DoE approach to propose an optimal design space in a quality-by-design (QbD) workflow to facilitate the HILIC method development. The mathematical QSRR-DoE model was shown to be highly predictive when applied to an independent test set of unseen compounds in unseen conditions with a RMSEP value of 5.83%. The QSRR-DoE computed retention time of pharmaceutical test analytes and subsequently calculated separation selectivity was used to optimize the chromatographic conditions for efficient separation of targets. A Monte Carlo simulation was performed to evaluate the risk of uncertainty in the model's prediction, and to define the design space where the desired quality criterion was met. Experimental realization of peak selectivity between targets under the selected optimal working conditions confirmed the theoretical predictions. These results demonstrate how discovery of optimal conditions for the separation of new analytes can be accelerated by the use of appropriate theoretical tools.
Interactions of Indole Derivatives with β-Cyclodextrin: A Quantitative Structure-Property Relationship Study

PubMed Central

Šoškić, Milan; Porobić, Ivana

2016-01-01

Retention factors for 31 indole derivatives, most of them with auxin activity, were determined by high-performance liquid chromatography, using bonded β-cyclodextrin as a stationary phase. A three-parameter QSPR (quantitative structure-property relationship) model, based on physico-chemical and structural descriptors was derived, which accounted for about 98% variations in the retention factors. The model suggests that the indole nucleus occupies the relatively apolar cavity of β-cyclodextrin while the carboxyl group of the indole -3-carboxylic acids makes hydrogen bonds with the hydroxyl groups of β-cyclodextrin. The length and flexibility of the side chain containing carboxyl group strongly affect the binding of these compounds to β-cyclodextrin. Non-acidic derivatives, unlike the indole-3-carboxylic acids, are poorly retained on the column. A reasonably well correlation was found between the retention factors of the indole-3-acetic acids and their relative binding affinities for human serum albumin, a carrier protein in the blood plasma. A less satisfactory correlation was obtained when the retention factors of the indole derivatives were compared with their affinities for auxin-binding protein 1, a plant auxin receptor. PMID:27124734
A strategy to improve the identification reliability of the chemical constituents by high-resolution mass spectrometry-based isomer structure prediction combined with a quantitative structure retention relationship analysis: Phthalide compounds in Chuanxiong as a test case.

PubMed

Zhang, Qingqing; Huo, Mengqi; Zhang, Yanling; Qiao, Yanjiang; Gao, Xiaoyan

2018-06-01

High-resolution mass spectrometry (HRMS) provides a powerful tool for the rapid analysis and identification of compounds in herbs. However, the diversity and large differences in the content of the chemical constituents in herbal medicines, especially isomerisms, are a great challenge for mass spectrometry-based structural identification. In the current study, a new strategy for the structural characterization of potential new phthalide compounds was proposed by isomer structure predictions combined with a quantitative structure-retention relationship (QSRR) analysis using phthalide compounds in Chuanxiong as an example. This strategy consists of three steps. First, the structures of phthalide compounds were reasonably predicted on the basis of the structure features and MS/MS fragmentation patterns: (1) the collected raw HRMS data were preliminarily screened by an in-house database; (2) the MS/MS fragmentation patterns of the analogous compounds were summarized; (3) the reported phthalide compounds were identified, and the structures of the isomers were reasonably predicted. Second, the QSRR model was established and verified using representative phthalide compound standards. Finally, the retention times of the predicted isomers were calculated by the QSRR model, and the structures of these peaks were rationally characterized by matching retention times of the detected chromatographic peaks and the predicted isomers. A multiple linear regression QSRR model in which 6 physicochemical variables were screened was built using 23 phthalide standards. The retention times of the phthalide isomers in Chuanxiong were well predicted by the QSRR model combined with reasonable structure predictions (R 2 =0.955). A total of 81 peaks were detected from Chuanxiong and assigned to reasonable structures, and 26 potential new phthalide compounds were structurally characterized. This strategy can improve the identification efficiency and reliability of homologues in complex
Molecular descriptor subset selection in theoretical peptide quantitative structure-retention relationship model development using nature-inspired optimization algorithms.

PubMed

Žuvela, Petar; Liu, J Jay; Macur, Katarzyna; Bączek, Tomasz

2015-10-06

In this work, performance of five nature-inspired optimization algorithms, genetic algorithm (GA), particle swarm optimization (PSO), artificial bee colony (ABC), firefly algorithm (FA), and flower pollination algorithm (FPA), was compared in molecular descriptor selection for development of quantitative structure-retention relationship (QSRR) models for 83 peptides that originate from eight model proteins. The matrix with 423 descriptors was used as input, and QSRR models based on selected descriptors were built using partial least squares (PLS), whereas root mean square error of prediction (RMSEP) was used as a fitness function for their selection. Three performance criteria, prediction accuracy, computational cost, and the number of selected descriptors, were used to evaluate the developed QSRR models. The results show that all five variable selection methods outperform interval PLS (iPLS), sparse PLS (sPLS), and the full PLS model, whereas GA is superior because of its lowest computational cost and higher accuracy (RMSEP of 5.534%) with a smaller number of variables (nine descriptors). The GA-QSRR model was validated initially through Y-randomization. In addition, it was successfully validated with an external testing set out of 102 peptides originating from Bacillus subtilis proteomes (RMSEP of 22.030%). Its applicability domain was defined, from which it was evident that the developed GA-QSRR exhibited strong robustness. All the sources of the model's error were identified, thus allowing for further application of the developed methodology in proteomics.
Quantitative structure-retention relationships applied to development of liquid chromatography gradient-elution method for the separation of sartans.

PubMed

Golubović, Jelena; Protić, Ana; Otašević, Biljana; Zečević, Mira

2016-04-01

QSRR are mathematically derived relationships between the chromatographic parameters determined for a representative series of analytes in given separation systems and the molecular descriptors accounting for the structural differences among the investigated analytes. Artificial neural network is a technique of data analysis, which sets out to emulate the human brain's way of working. The aim of the present work was to optimize separation of six angiotensin receptor antagonists, so-called sartans: losartan, valsartan, irbesartan, telmisartan, candesartan cilexetil and eprosartan in a gradient-elution HPLC method. For this purpose, ANN as a mathematical tool was used for establishing a QSRR model based on molecular descriptors of sartans and varied instrumental conditions. The optimized model can be further used for prediction of an external congener of sartans and analysis of the influence of the analyte structure, represented through molecular descriptors, on retention behaviour. Molecular descriptors included in modelling were electrostatic, geometrical and quantum-chemical descriptors: connolly solvent excluded volume non-1,4 van der Waals energy, octanol/water distribution coefficient, polarizability, number of proton-donor sites and number of proton-acceptor sites. Varied instrumental conditions were gradient time, buffer pH and buffer molarity. High prediction ability of the optimized network enabled complete separation of the analytes within the run time of 15.5 min under following conditions: gradient time of 12.5 min, buffer pH of 3.95 and buffer molarity of 25 mM. Applied methodology showed the potential to predict retention behaviour of an external analyte with the properties within the training space. Connolly solvent excluded volume, polarizability and number of proton-acceptor sites appeared to be most influential paramateres on retention behaviour of the sartans. Copyright © 2015 Elsevier B.V. All rights reserved.

A Quantitative Structure-Property Relationship (QSPR) Study of Aliphatic Alcohols by the Method of Dividing the Molecular Structure into Substructure

PubMed Central

Liu, Fengping; Cao, Chenzhong; Cheng, Bin

2011-01-01

A quantitative structure–property relationship (QSPR) analysis of aliphatic alcohols is presented. Four physicochemical properties were studied: boiling point (BP), n-octanol–water partition coefficient (lg POW), water solubility (lg W) and the chromatographic retention indices (RI) on different polar stationary phases. In order to investigate the quantitative structure–property relationship of aliphatic alcohols, the molecular structure ROH is divided into two parts, R and OH to generate structural parameter. It was proposed that the property is affected by three main factors for aliphatic alcohols, alkyl group R, substituted group OH, and interaction between R and OH. On the basis of the polarizability effect index (PEI), previously developed by Cao, the novel molecular polarizability effect index (MPEI) combined with odd-even index (OEI), the sum eigenvalues of bond-connecting matrix (SX1CH) previously developed in our team, were used to predict the property of aliphatic alcohols. The sets of molecular descriptors were derived directly from the structure of the compounds based on graph theory. QSPR models were generated using only calculated descriptors and multiple linear regression techniques. These QSPR models showed high values of multiple correlation coefficient (R > 0.99) and Fisher-ratio statistics. The leave-one-out cross-validation demonstrated the final models to be statistically significant and reliable. PMID:21731451
Partitioning and lipophilicity in quantitative structure-activity relationships.

PubMed Central

Dearden, J C

1985-01-01

The history of the relationship of biological activity to partition coefficient and related properties is briefly reviewed. The dominance of partition coefficient in quantitation of structure-activity relationships is emphasized, although the importance of other factors is also demonstrated. Various mathematical models of in vivo transport and binding are discussed; most of these involve partitioning as the primary mechanism of transport. The models describe observed quantitative structure-activity relationships (QSARs) well on the whole, confirming that partitioning is of key importance in in vivo behavior of a xenobiotic. The partition coefficient is shown to correlate with numerous other parameters representing bulk, such as molecular weight, volume and surface area, parachor and calculated indices such as molecular connectivity; this is especially so for apolar molecules, because for polar molecules lipophilicity factors into both bulk and polar or hydrogen bonding components. The relationship of partition coefficient to chromatographic parameters is discussed, and it is shown that such parameters, which are often readily obtainable experimentally, can successfully supplant partition coefficient in QSARs. The relationship of aqueous solubility with partition coefficient is examined in detail. Correlations are observed, even with solid compounds, and these can be used to predict solubility. The additive/constitutive nature of partition coefficient is discussed extensively, as are the available schemes for the calculation of partition coefficient. Finally the use of partition coefficient to provide structural information is considered. It is shown that partition coefficient can be a valuable structural tool, especially if the enthalpy and entropy of partitioning are available. PMID:3905374
In silico quantitative structure-toxicity relationship study of aromatic nitro compounds.

PubMed

Pasha, Farhan Ahmad; Neaz, Mohammad Morshed; Cho, Seung Joo; Ansari, Mohiuddin; Mishra, Sunil Kumar; Tiwari, Sharvan

2009-05-01

Small molecules often have toxicities that are a function of molecular structural features. Minor variations in structural features can make large difference in such toxicity. Consequently, in silico techniques may be used to correlate such molecular toxicities with their structural features. Relative to nine different sets of aromatic nitro compounds having known observed toxicities against different targets, we developed ligand-based 2D quantitative structure-toxicity relationship models using 20 selected topological descriptors. The topological descriptors have several advantages such as conformational independency, facile and less time-consuming computation to yield good results. Multiple linear regression analysis was used to correlate variations of toxicity with molecular properties. The information index on molecular size, lopping centric index and Kier flexibility index were identified as fundamental descriptors for different kinds of toxicity, and further showed that molecular size, branching and molecular flexibility might be particularly important factors in quantitative structure-toxicity relationship analysis. This study revealed that topological descriptor-guided quantitative structure-toxicity relationship provided a very useful, cost and time-efficient, in silico tool for describing small-molecule toxicities.
Quantitative structure-activity relationship modeling on in vitro endocrine effects and metabolic stability involving 26 selected brominated flame retardants.

PubMed

Harju, Mikael; Hamers, Timo; Kamstra, Jorke H; Sonneveld, Edwin; Boon, Jan P; Tysklind, Mats; Andersson, Patrik L

2007-04-01

In this work, quantitative structure-activity relationships (QSARs) were developed to aid human and environmental risk assessment processes for brominated flame retardants (BFRs). Brominated flame retardants, such as the high-production-volume chemicals polybrominated diphenyl ethers (PBDEs), tetrabromobisphenol A, and hexabromocyclododecane, have been identified as potential endocrine disruptors. Quantitative structure-activity relationship models were built based on the in vitro potencies of 26 selected BFRs. The in vitro assays included interactions with, for example, androgen, progesterone, estrogen, and dioxin (aryl hydrocarbon) receptor, plus competition with thyroxine for its plasma carrier protein (transthyretin), inhibition of estradiol sulfation via sulfotransferase, and finally, rate of metabolization. The QSAR modeling, a number of physicochemical parameters were calculated describing the electronic, lipophilic, and structural characteristics of the molecules. These include frontier molecular orbitals, molecular charges, polarities, log octanol/water partitioning coefficient, and two- and three-dimensional molecularproperties. Experimental properties were included and measured for PBDEs, such as their individual ultraviolet spectra (200-320 nm) and retention times on three different high-performance liquid chromatography columns and one nonpolar gas chromatography column. Quantitative structure-activity relationship models based on androgen antagonism and metabolic degradation rates generally gave similar results, suggesting that lower-brominated PBDEs with bromine substitutions in ortho positions and bromine-free meta- and para positions had the highest potencies and metabolic degradation rates. Predictions made for the constituents of the technical flame retardant Bromkal 70-5DE found BDE 17 to be a potent androgen antagonist and BDE 66, which is a relevant PBDE in environmental samples, to be only a weak antagonist.
Liquid chromatography coupled to quadrupole-time of flight tandem mass spectrometry based quantitative structure-retention relationships of amino acid analogues derivatized via n-propyl chloroformate mediated reaction.

PubMed

Kritikos, Nikolaos; Tsantili-Kakoulidou, Anna; Loukas, Yannis L; Dotsikas, Yannis

2015-07-17

In the current study, quantitative structure-retention relationships (QSRR) were constructed based on data obtained by a LC-(ESI)-QTOF-MS/MS method for the determination of amino acid analogues, following their derivatization via chloroformate esters. Molecules were derivatized via n-propyl chloroformate/n-propanol mediated reaction. Derivatives were acquired through a liquid-liquid extraction procedure. Chromatographic separation is based on gradient elution using methanol/water mixtures from a 70/30% composition to an 85/15% final one, maintaining a constant rate of change. The group of examined molecules was diverse, including mainly α-amino acids, yet also β- and γ-amino acids, γ-amino acid analogues, decarboxylated and phosphorylated analogues and dipeptides. Projection to latent structures (PLS) method was selected for the formation of QSRRs, resulting in a total of three PLS models with high cross-validated coefficients of determination Q(2)Y. For this reason, molecular structures were previously described through the use of descriptors. Through stratified random sampling procedures, 57 compounds were split to a training set and a test set. Model creation was based on multiple criteria including principal component significance and eigenvalue, variable importance, form of residuals, etc. Validation was based on statistical metrics Rpred(2),QextF2(2),QextF3(2) for the test set and Roy's metrics rm(Av)(2) and rm(δ)(2), assessing both predictive stability and internal validity. Based on aforementioned models, simplified equivalent were then created using a multi-linear regression (MLR) method. MLR models were also validated with the same metrics. The suggested models are considered useful for the estimation of retention times of amino acid analogues for a series of applications. Copyright © 2015 Elsevier B.V. All rights reserved.
Effect of substituents on prediction of TLC retention of tetra-dentate Schiff bases and their Copper(II) and Nickel(II) complexes.

PubMed

Stevanović, Nikola R; Perušković, Danica S; Gašić, Uroš M; Antunović, Vesna R; Lolić, Aleksandar Đ; Baošić, Rada M

2017-03-01

The objectives of this study were to gain insights into structure-retention relationships and to propose the model to estimating their retention. Chromatographic investigation of series of 36 Schiff bases and their copper(II) and nickel(II) complexes was performed under both normal- and reverse-phase conditions. Chemical structures of the compounds were characterized by molecular descriptors which are calculated from the structure and related to the chromatographic retention parameters by multiple linear regression analysis. Effects of chelation on retention parameters of investigated compounds, under normal- and reverse-phase chromatographic conditions, were analyzed by principal component analysis, quantitative structure-retention relationship and quantitative structure-activity relationship models were developed on the basis of theoretical molecular descriptors, calculated exclusively from molecular structure, and parameters of retention and lipophilicity. Copyright © 2016 John Wiley & Sons, Ltd.
PREDICTING TOXICOLOGICAL ENDPOINTS OF CHEMICALS USING QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIPS (QSARS)

EPA Science Inventory

Quantitative structure-activity relationships (QSARs) are being developed to predict the toxicological endpoints for untested chemicals similar in structure to chemicals that have known experimental toxicological data. Based on a very large number of predetermined descriptors, a...
Quantitative structure-property relationship (correlation analysis) of phosphonic acid-based chelates in design of MRI contrast agent.

PubMed

Tiwari, Anjani K; Ojha, Himanshu; Kaul, Ankur; Dutta, Anupama; Srivastava, Pooja; Shukla, Gauri; Srivastava, Rakesh; Mishra, Anil K

2009-07-01

Nuclear magnetic resonance imaging is a very useful tool in modern medical diagnostics, especially when gadolinium (III)-based contrast agents are administered to the patient with the aim of increasing the image contrast between normal and diseased tissues. With the use of soft modelling techniques such as quantitative structure-activity relationship/quantitative structure-property relationship after a suitable description of their molecular structure, we have studied a series of phosphonic acid for designing new MRI contrast agent. Quantitative structure-property relationship studies with multiple linear regression analysis were applied to find correlation between different calculated molecular descriptors of the phosphonic acid-based chelating agent and their stability constants. The final quantitative structure-property relationship mathematical models were found as--quantitative structure-property relationship Model for phosphonic acid series (Model 1)--log K(ML) = {5.00243(+/-0.7102)}- MR {0.0263(+/-0.540)}n = 12 l r l = 0.942 s = 0.183 F = 99.165 quantitative structure-property relationship Model for phosphonic acid series (Model 2)--log K(ML) = {5.06280(+/-0.3418)}- MR {0.0252(+/- .198)}n = 12 l r l = 0.956 s = 0.186 F = 99.256.
Correlation between structure, retention, property, and activity of biologically relevant 1,7-bis(aminoalkyl)diazachrysene derivatives.

PubMed

Šegan, Sandra; Trifković, Jelena; Verbić, Tatjana; Opsenica, Dejan; Zlatović, Mario; Burnett, James; Šolaja, Bogdan; Milojković-Opsenica, Dušanka

2013-01-01

The physicochemical properties, retention parameters (R(M)(0)), partition coefficients (logP(OW)), and pK(a) values for a series of thirteen 1,7-bis(aminoalkyl) diazachrysene (1,7-DAAC) derivatives were determined in order to reveal the characteristics responsible for their biological behavior. The investigated compounds inhibit three unrelated pathogens (the Botulinum neurotoxin serotype A light chain (BoNT/A LC), Plasmodium falciparum malaria, and Ebola filovirus) via three different mechanisms of action. To determine the most influential factors governing the retention and activities of the investigated diazachrysenes, R(M)(0), logP(OW), and biological activity values were correlated with 2D and 3D molecular descriptors, using a partial least squares regression. The resulting quantitative structure-retention (property) relationships indicate the importance of descriptors related to the hydrophobicity of the molecules (e.g., predicted partition coefficients and hydrophobic surface area). Quantitative structure-activity relationship models for describing biological activity against the BoNT/A LC and malarial strains also include overall compound polarity, electron density distribution, and proton donor/acceptor potential. Furthermore, models for Ebola filovirus inhibition are presented qualitatively to provide insights into parameters that may contribute to the compounds' antiviral activities. Overall, the models form the basis for selecting structural features that significantly affect the compound's absorption, distribution, metabolism, excretion, and toxicity profiles. Copyright © 2012 Elsevier B.V. All rights reserved.
QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIPS FOR CHEMICAL REDUCTIONS OF ORGANIC CONTAMINANTS

EPA Science Inventory

Sufficient kinetic data on abiotic reduction reactions involving organic contaminants are now available that quantitative structure-activity relationships (QSARs) for these reactions can be developed. Over 50 QSARs have been reported, most in just the last few years, and they ar...
Academic Advising and First-Generation College Students: A Quantitative Study on Student Retention

ERIC Educational Resources Information Center

Swecker, Hadyn K.; Fifolt, Matthew; Searby, Linda

2014-01-01

For this quantitative study, we used a multiple logistic regression technique to investigate the relationship between the number of meetings with an academic advisor and retention of first-generation students, as represented by enrollment status and academic standing at a large, public research institution in the Southeast. Consistent with…
Establishment of quantitative retention-activity model by optimized microemulsion liquid chromatography.

PubMed

Xu, Liyuan; Gao, Haoshi; Li, Liangxing; Li, Yinnong; Wang, Liuyun; Gao, Chongkai; Li, Ning

2016-12-23

The effective permeability coefficient is of theoretical and practical importance in evaluation of the bioavailability of drug candidates. However, most methods currently used to measure this coefficient are expensive and time-consuming. In this paper, we addressed these problems by proposing a new measurement method which is based on the microemulsion liquid chromatography. First, the parallel artificial membrane permeability assays model was used to determine the effective permeability of drug so that quantitative retention-activity relationships could be established, which were used to optimize the microemulsion liquid chromatography. The most effective microemulsion system used a mobile phase of 6.0% (w/w) Brij35, 6.6% (w/w) butanol, 0.8% (w/w) octanol, and 86.6% (w/w) phosphate buffer (pH 7.4). Next, support vector machine and back-propagation neural networks are employed to develop a quantitative retention-activity relationships model associated with the optimal microemulsion system, and used to improve the prediction ability. Finally, an adequate correlation between experimental value and predicted value is computed to verify the performance of the optimal model. The results indicate that the microemulsion liquid chromatography can serve as a possible alternative to the PAMPA method for determination of high-throughput permeability and simulation of biological processes. Copyright © 2016. Published by Elsevier B.V.
Retention of Nontraditional Students: A Quantitative Research Study

ERIC Educational Resources Information Center

Nichols, Shirley J.

2009-01-01

The purpose of this quantitative correlational research study was to investigate, describe, and measure factors influencing retention of nontraditional first and second year students at a university located in the Midwestern United States. Retention of adult students has become a major issue for many institutions of higher education and many…
Molecular structure and gas chromatographic retention behavior of the components of Ylang-Ylang oil.

PubMed

Olivero, J; Gracia, T; Payares, P; Vivas, R; Díaz, D; Daza, E; Geerlings, P

1997-05-01

Using quantitative structure-retention relationships (QSRR) methodologies the Kovats gas chromatographic retention indices for both apolar (DB-1) and polar (DB-Wax) columns for 48 compounds from Ylang-Ylang essential oil were empirically predicted from calculated and experimental data on molecular structure. Topological, geometric, and electronic descriptors were obtained for model generation. Relationships between descriptors and the retention data reported were established by linear multiple regression, giving equations that can be used to predict the Kovats indices for compounds present in essential oils, both in DB-1 and DB-Wax columns. Factor analysis was performed to interpret the meaning of the descriptors included in the models. The prediction model for the DB-1 column includes descriptors such as Randic's first-order connectivity index (1X), the molecular surface (MSA), the sum of the atomic charge on all the hydrogens (QH), Randic's third-order connectivity index (3X) and the molecular electronegativity (chi). The prediction model for the DB-Wax column includes the first three descriptors mentioned for the DB-1 column (1X, MSA and QH) and the most negative charge (MNC), the global softness (S), and the difference between Randic's and Kier and Hall's third-order connectivity indexes (3X-3XV).
Quantitative structure-antifungal activity relationships of some benzohydrazides against Botrytis cinerea.

PubMed

Reino, José L; Saiz-Urra, Liane; Hernandez-Galan, Rosario; Aran, Vicente J; Hitchcock, Peter B; Hanson, James R; Gonzalez, Maykel Perez; Collado, Isidro G

2007-06-27

Fourteen benzohydrazides have been synthesized and evaluated for their in vitro antifungal activity against the phytopathogenic fungus Botrytis cinerea. The best antifungal activity was observed for the N',N'-dibenzylbenzohydrazides 3b-d and for the N-aminoisoindoline-derived benzohydrazide 5. A quantitative structure-activity relationship (QSAR) study has been developed using a topological substructural molecular design (TOPS-MODE) approach to interpret the antifungal activity of these synthetic compounds. The model described 98.3% of the experimental variance, with a standard deviation of 4.02. The influence of an ortho substituent on the conformation of the benzohydrazides was investigated by X-ray crystallography and supported by QSAR study. Several aspects of the structure-activity relationships are discussed in terms of the contribution of different bonds to the antifungal activity, thereby making the relationships between structure and biological activity more transparent.
Quantitative Structure--Activity Relationship Modeling of Rat Acute Toxicity by Oral Exposure

EPA Science Inventory

Background: Few Quantitative Structure-Activity Relationship (QSAR) studies have successfully modeled large, diverse rodent toxicity endpoints. Objective: In this study, a combinatorial QSAR approach has been employed for the creation of robust and predictive models of acute toxi...
Quantitative Structure-Antifungal Activity Relationships for cinnamate derivatives.

PubMed

Saavedra, Laura M; Ruiz, Diego; Romanelli, Gustavo P; Duchowicz, Pablo R

2015-12-01

Quantitative Structure-Activity Relationships (QSAR) are established with the aim of analyzing the fungicidal activities of a set of 27 active cinnamate derivatives. The exploration of more than a thousand of constitutional, topological, geometrical and electronic molecular descriptors, which are calculated with Dragon software, leads to predictions of the growth inhibition on Pythium sp and Corticium rolfsii fungi species, in close agreement to the experimental values extracted from the literature. A set containing 21 new structurally related cinnamate compounds is prepared. The developed QSAR models are applied to predict the unknown fungicidal activity of this set, showing that cinnamates like 38, 28 and 42 are expected to be highly active for Pythium sp, while this is also predicted for 28 and 34 in C. rolfsii. Copyright © 2015 Elsevier Inc. All rights reserved.
Electron-density descriptors as predictors in quantitative structure--activity/property relationships and drug design.

PubMed

Matta, Chérif F; Arabi, Alya A

2011-06-01

The use of electron density-based molecular descriptors in drug research, particularly in quantitative structure--activity relationships/quantitative structure--property relationships studies, is reviewed. The exposition starts by a discussion of molecular similarity and transferability in terms of the underlying electron density, which leads to a qualitative introduction to the quantum theory of atoms in molecules (QTAIM). The starting point of QTAIM is the topological analysis of the molecular electron-density distributions to extract atomic and bond properties that characterize every atom and bond in the molecule. These atomic and bond properties have considerable potential as bases for the construction of robust quantitative structure--activity/property relationships models as shown by selected examples in this review. QTAIM is applicable to the electron density calculated from quantum-chemical calculations and/or that obtained from ultra-high resolution x-ray diffraction experiments followed by nonspherical refinement. Atomic and bond properties are introduced followed by examples of application of each of these two families of descriptors. The review ends with a study whereby the molecular electrostatic potential, uniquely determined by the density, is used in conjunction with atomic properties to elucidate the reasons for the biological similarity of bioisosteres.
Quantitative structure-toxicity relationship (QSTR) studies on the organophosphate insecticides.

PubMed

Can, Alper

2014-11-04

Organophosphate insecticides are the most commonly used pesticides in the world. In this study, quantitative structure-toxicity relationship (QSTR) models were derived for estimating the acute oral toxicity of organophosphate insecticides to male rats. The 20 chemicals of the training set and the seven compounds of the external testing set were described by means of using descriptors. Descriptors for lipophilicity, polarity and molecular geometry, as well as quantum chemical descriptors for energy were calculated. Model development to predict toxicity of organophosphate insecticides in different matrices was carried out using multiple linear regression. The model was validated internally and externally. In the present study, QSTR model was used for the first time to understand the inherent relationships between the organophosphate insecticide molecules and their toxicity behavior. Such studies provide mechanistic insight about structure-toxicity relationship and help in the design of less toxic insecticides. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.
An advanced application of the quantitative structure-activity relationship concept in electrokinetic chromatography of metal complexes.

PubMed

Oszwałdowski, Sławomir; Timerbaev, Andrei R

2008-02-01

The relevance of the quantitative structure-activity relationship (QSAR) principle in MEKC and microemulsion EKC (MEEKC) of metal-ligand complexes was evaluated for a better understanding of analyte migration mechanism. A series of gallium chelates were applied as test solutes with available experimental migration data in order to reveal the molecular properties that govern the separation. The QSAR models operating with n-octanol-water partition coefficients or van der Waals volumes were found to be valid for estimation of the retention factors (log k') of neutral compounds when using only an aqueous MEEKC electrolyte. On the other hand, consistent approximations of log k' for both uncharged and charged complexes in either EKC mode (and also with hydro-organic BGEs) were achievable with two-parametric QSARs in which the dipole moment is additionally incorporated as a structural descriptor, reflecting the electrostatic solute-pseudostationary phase interaction. The theoretical analysis of significant molecular parameters in MEKC systems, in which the micellar BGE is modified with an organic solvent, confirmed that concomitant consideration of hydrophobic, electrostatic, and solvation factors is essential for explaining the migration behavior of neutral metal complexes.

Prediction of the retention of s-triazines in reversed-phase high-performance liquid chromatography under linear gradient-elution conditions.

PubMed

D'Archivio, Angelo Antonio; Maggi, Maria Anna; Ruggieri, Fabrizio

2014-08-01

In this paper, a multilayer artificial neural network is used to model simultaneously the effect of solute structure and eluent concentration profile on the retention of s-triazines in reversed-phase high-performance liquid chromatography under linear gradient elution. The retention data of 24 triazines, including common herbicides and their metabolites, are collected under 13 different elution modes, covering the following experimental domain: starting acetonitrile volume fraction ranging between 40 and 60% and gradient slope ranging between 0 and 1% acetonitrile/min. The gradient parameters together with five selected molecular descriptors, identified by quantitative structure-retention relationship modelling applied to individual separation conditions, are the network inputs. Predictive performance of this model is evaluated on six external triazines and four unseen separation conditions. For comparison, retention of triazines is modelled by both quantitative structure-retention relationships and response surface methodology, which describe separately the effect of molecular structure and gradient parameters on the retention. Although applied to a wider variable domain, the network provides a performance comparable to that of the above "local" models and retention times of triazines are modelled with accuracy generally better than 7%. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Quantitative structure carcinogenicity relationship for detecting structural alerts in nitroso-compounds

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

Helguera, Aliuska Morales; Molecular Simulation and Drug Design, Chemical Bioactive Center, Central University of Las Villas, Santa Clara, 54830, Villa Clara; Department of Chemistry, Central University of Las Villas, Santa Clara, 54830, Villa Clara

2008-09-01

In this work, Quantitative Structure-Activity Relationship (QSAR) modelling was used as a tool for predicting the carcinogenic potency of a set of 39 nitroso-compounds, which have been bioassayed in male rats by using the oral route of administration. The optimum QSAR model provided evidence of good fit and performance of predicitivity from training set. It was able to account for about 84% of the variance in the experimental activity and exhibited high values of the determination coefficients of cross validations, leave one out and bootstrapping (q{sup 2}{sub LOO} = 78.53 and q{sup 2}{sub Boot} = 74.97). Such a model wasmore » based on spectral moments weighted with Gasteiger-Marsilli atomic charges, polarizability and hydrophobicity, as well as with Abraham indexes, specifically the summation solute hydrogen bond basicity and the combined dipolarity/polarizability. This is the first study to have explored the possibility of combining Abraham solute descriptors with spectral moments. A reasonable interpretation of these molecular descriptors from a toxicological point of view was achieved by means of taking into account bond contributions. The set of relationships so derived revealed the importance of the length of the alkyl chains for determining carcinogenic potential of the chemicals analysed, and were able to explain the difference between mono-substituted and di-substituted nitrosoureas as well as to discriminate between isomeric structures with hydroxyl-alkyl and alkyl substituents in different positions. Moreover, they allowed the recognition of structural alerts in classical structures of two potent nitrosamines, consistent with their biotransformation. These results indicate that this new approach has the potential for improving carcinogenicity predictions based on the identification of structural alerts.« less
Chemical Sensor Array Response Modeling Using Quantitative Structure-Activity Relationships Technique

NASA Astrophysics Data System (ADS)

Shevade, Abhijit V.; Ryan, Margaret A.; Homer, Margie L.; Zhou, Hanying; Manfreda, Allison M.; Lara, Liana M.; Yen, Shiao-Pin S.; Jewell, April D.; Manatt, Kenneth S.; Kisor, Adam K.

We have developed a Quantitative Structure-Activity Relationships (QSAR) based approach to correlate the response of chemical sensors in an array with molecular descriptors. A novel molecular descriptor set has been developed; this set combines descriptors of sensing film-analyte interactions, representing sensor response, with a basic analyte descriptor set commonly used in QSAR studies. The descriptors are obtained using a combination of molecular modeling tools and empirical and semi-empirical Quantitative Structure-Property Relationships (QSPR) methods. The sensors under investigation are polymer-carbon sensing films which have been exposed to analyte vapors at parts-per-million (ppm) concentrations; response is measured as change in film resistance. Statistically validated QSAR models have been developed using Genetic Function Approximations (GFA) for a sensor array for a given training data set. The applicability of the sensor response models has been tested by using it to predict the sensor activities for test analytes not considered in the training set for the model development. The validated QSAR sensor response models show good predictive ability. The QSAR approach is a promising computational tool for sensing materials evaluation and selection. It can also be used to predict response of an existing sensing film to new target analytes.
Building Relationships between Business Schools and Students: An Empirical Investigation into Student Retention

ERIC Educational Resources Information Center

Adidam, Phani Tej; Bingi, R. Prasad; Sindhav, Birud

2004-01-01

This study uses the relationship marketing theory of commitment and trust as a framework to investigate the issue of student retention in business schools. Structural equation modeling was used to examine relationships specified by Morgan and Hunt's (1994) theory of relationship marketing. Students' commitment to the business schools were…
Quantitative structure-property relationship modeling of Grätzel solar cell dyes.

PubMed

Venkatraman, Vishwesh; Åstrand, Per-Olof; Alsberg, Bjørn Kåre

2014-01-30

With fossil fuel reserves on the decline, there is increasing focus on the design and development of low-cost organic photovoltaic devices, in particular, dye-sensitized solar cells (DSSCs). The power conversion efficiency (PCE) of a DSSC is heavily influenced by the chemical structure of the dye. However, as far as we know, no predictive quantitative structure-property relationship models for DSSCs with PCE as one of the response variables have been reported. Thus, we report for the first time the successful application of comparative molecular field analysis (CoMFA) and vibrational frequency-based eigenvalue (EVA) descriptors to model molecular structure-photovoltaic performance relationships for a set of 40 coumarin derivatives. The results show that the models obtained provide statistically robust predictions of important photovoltaic parameters such as PCE, the open-circuit voltage (V(OC)), short-circuit current (J(SC)) and the peak absorption wavelength λ(max). Some of our findings based on the analysis of the models are in accordance with those reported in the literature. These structure-property relationships can be applied to the rational structural design and evaluation of new photovoltaic materials. Copyright © 2013 Wiley Periodicals, Inc.
3D-quantitative structure-activity relationship study for the design of novel enterovirus A71 3C protease inhibitors.

PubMed

Nie, Quandeng; Xu, Xiaoyi; Zhang, Qi; Ma, Yuying; Yin, Zheng; Shang, Luqing

2018-06-07

A three-dimensional quantitative structure-activity relationships model of enterovirus A71 3C protease inhibitors was constructed in this study. The protein-ligand interaction fingerprint was analyzed to generate a pharmacophore model. A predictive and reliable three-dimensional quantitative structure-activity relationships model was built based on the Flexible Alignment of AutoGPA. Moreover, three novel compounds (I-III) were designed and evaluated for their biochemical activity against 3C protease and anti-enterovirus A71 activity in vitro. III exhibited excellent inhibitory activity (IC 50 =0.031 ± 0.005 μM, EC 50 =0.036 ± 0.007 μM). Thus, this study provides a useful quantitative structure-activity relationships model to develop potent inhibitors for enterovirus A71 3C protease. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.
Computational modeling approaches to quantitative structure-binding kinetics relationships in drug discovery.

PubMed

De Benedetti, Pier G; Fanelli, Francesca

2018-03-21

Simple comparative correlation analyses and quantitative structure-kinetics relationship (QSKR) models highlight the interplay of kinetic rates and binding affinity as an essential feature in drug design and discovery. The choice of the molecular series, and their structural variations, used in QSKR modeling is fundamental to understanding the mechanistic implications of ligand and/or drug-target binding and/or unbinding processes. Here, we discuss the implications of linear correlations between kinetic rates and binding affinity constants and the relevance of the computational approaches to QSKR modeling. Copyright © 2018 Elsevier Ltd. All rights reserved.
Quantitative structure-activation barrier relationship modeling for Diels-Alder ligations utilizing quantum chemical structural descriptors.

PubMed

Nandi, Sisir; Monesi, Alessandro; Drgan, Viktor; Merzel, Franci; Novič, Marjana

2013-10-30

In the present study, we show the correlation of quantum chemical structural descriptors with the activation barriers of the Diels-Alder ligations. A set of 72 non-catalysed Diels-Alder reactions were subjected to quantitative structure-activation barrier relationship (QSABR) under the framework of theoretical quantum chemical descriptors calculated solely from the structures of diene and dienophile reactants. Experimental activation barrier data were obtained from literature. Descriptors were computed using Hartree-Fock theory using 6-31G(d) basis set as implemented in Gaussian 09 software. Variable selection and model development were carried out by stepwise multiple linear regression methodology. Predictive performance of the quantitative structure-activation barrier relationship (QSABR) model was assessed by training and test set concept and by calculating leave-one-out cross-validated Q2 and predictive R2 values. The QSABR model can explain and predict 86.5% and 80% of the variances, respectively, in the activation energy barrier training data. Alternatively, a neural network model based on back propagation of errors was developed to assess the nonlinearity of the sought correlations between theoretical descriptors and experimental reaction barriers. A reasonable predictability for the activation barrier of the test set reactions was obtained, which enabled an exploration and interpretation of the significant variables responsible for Diels-Alder interaction between dienes and dienophiles. Thus, studies in the direction of QSABR modelling that provide efficient and fast prediction of activation barriers of the Diels-Alder reactions turn out to be a meaningful alternative to transition state theory based computation.
Fragment-based quantitative structure-activity relationship (FB-QSAR) for fragment-based drug design.

PubMed

Du, Qi-Shi; Huang, Ri-Bo; Wei, Yu-Tuo; Pang, Zong-Wen; Du, Li-Qin; Chou, Kuo-Chen

2009-01-30

In cooperation with the fragment-based design a new drug design method, the so-called "fragment-based quantitative structure-activity relationship" (FB-QSAR) is proposed. The essence of the new method is that the molecular framework in a family of drug candidates are divided into several fragments according to their substitutes being investigated. The bioactivities of molecules are correlated with the physicochemical properties of the molecular fragments through two sets of coefficients in the linear free energy equations. One coefficient set is for the physicochemical properties and the other for the weight factors of the molecular fragments. Meanwhile, an iterative double least square (IDLS) technique is developed to solve the two sets of coefficients in a training data set alternately and iteratively. The IDLS technique is a feedback procedure with machine learning ability. The standard Two-dimensional quantitative structure-activity relationship (2D-QSAR) is a special case, in the FB-QSAR, when the whole molecule is treated as one entity. The FB-QSAR approach can remarkably enhance the predictive power and provide more structural insights into rational drug design. As an example, the FB-QSAR is applied to build a predictive model of neuraminidase inhibitors for drug development against H5N1 influenza virus. (c) 2008 Wiley Periodicals, Inc.
Structure modification and functionality of whey proteins: quantitative structure-activity relationship approach.

PubMed

Nakai, S; Li-Chan, E

1985-10-01

According to the original idea of quantitative structure-activity relationship, electric, hydrophobic, and structural parameters should be taken into consideration for elucidating functionality. Changes in these parameters are reflected in the property of protein solubility upon modification of whey proteins by heating. Although solubility is itself a functional property, it has been utilized to explain other functionalities of proteins. However, better correlations were obtained when hydrophobic parameters of the proteins were used in conjunction with solubility. Various treatments reported in the literature were applied to whey protein concentrate in an attempt to obtain whipping and gelling properties similar to those of egg white. Mapping simplex optimization was used to search for the best results. Improvement in whipping properties by pepsin hydrolysis may have been due to higher protein solubility, and good gelling properties resulting from polyphosphate treatment may have been due to an increase in exposable hydrophobicity. However, the results of angel food cake making were still unsatisfactory.
Quantitative Structure-Cytotoxicity Relationship of Oleoylamides.

PubMed

Sakagami, Hiroshi; Uesawa, Yoshihiro; Ishihara, Mariko; Kagaya, Hajime; Kanamoto, Taisei; Terakubo, Shigemi; Nakashima, Hideki; Takao, Koichi; Sugita, Yoshiaki

2015-10-01

Eighteen oleoylamides were subjected to quantitative structure-activity relationship analysis based on their cytotoxicity, tumor selectivity and anti-HIV activity, in order to assess their biological activities. Cytotoxicity against four human oral squamous cell carcinoma (OSCC) cell lines and five human oral normal cells (gingival fibroblast, periodontal ligament fibroblast, pulp cell, oral keratinocyte, primary gingival epithelial cells) was determined by the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) method. Tumor-selectivity (TS) was evaluated by the ratio of the mean 50% cytotoxic concentration (CC50) against normal human oral cells to that against OSCC cell lines. Potency-selectivity expression (PSE) was determined by the ratio of TS to CC50 against OSCC. Anti-HIV activity was evaluated by the ratio of CC50 to the concentration leading to 50% cytoprotection from HIV infection (EC50). Physicochemical, structural and quantum-chemical parameters were calculated based on the conformations optimized by the LowModeMD method. Among 18 derivatives, compounds 8: with a catechol group) and 18: with a (2-pyridyl)amino group) had the highest TS. On the other hand, doxorubicin and 5-fluorouracil (5-FU) were more highly cytotoxic to normal epithelial cells, displaying unexpectedly lower TS and PSE values. None of the compounds had anti-HIV activity. Among 330 chemical descriptors, 75, 73 and 19 descriptors significantly correlated to the cytotoxicity to normal and tumor cells, and TS, respectively. Multivariate statistics with chemical descriptors for molecular polarization and hydrophobicity may be useful for the evaluation of cytotoxicity and TS of oleoylamides. Copyright© 2015 International Institute of Anticancer Research (Dr. John G. Delinassios), All rights reserved.
Quantitative structure activity relationship studies of mushroom tyrosinase inhibitors

NASA Astrophysics Data System (ADS)

Xue, Chao-Bin; Luo, Wan-Chun; Ding, Qi; Liu, Shou-Zhu; Gao, Xing-Xiang

2008-05-01

Here, we report our results from quantitative structure-activity relationship studies on tyrosinase inhibitors. Interactions between benzoic acid derivatives and tyrosinase active sites were also studied using a molecular docking method. These studies indicated that one possible mechanism for the interaction between benzoic acid derivatives and the tyrosinase active site is the formation of a hydrogen-bond between the hydroxyl (aOH) and carbonyl oxygen atoms of Tyr98, which stabilized the position of Tyr98 and prevented Tyr98 from participating in the interaction between tyrosinase and ORF378. Tyrosinase, also known as phenoloxidase, is a key enzyme in animals, plants and insects that is responsible for catalyzing the hydroxylation of tyrosine into o-diphenols and the oxidation of o-diphenols into o-quinones. In the present study, the bioactivities of 48 derivatives of benzaldehyde, benzoic acid, and cinnamic acid compounds were used to construct three-dimensional quantitative structure-activity relationship (3D-QSAR) models using comparative molecular field (CoMFA) and comparative molecular similarity indices (CoMSIA) analyses. After superimposition using common substructure-based alignments, robust and predictive 3D-QSAR models were obtained from CoMFA ( q 2 = 0.855, r 2 = 0.978) and CoMSIA ( q 2 = 0.841, r 2 = 0.946), with 6 optimum components. Chemical descriptors, including electronic (Hammett σ), hydrophobic (π), and steric (MR) parameters, hydrogen bond acceptor (H-acc), and indicator variable ( I), were used to construct a 2D-QSAR model. The results of this QSAR indicated that π, MR, and H-acc account for 34.9, 31.6, and 26.7% of the calculated biological variance, respectively. The molecular interactions between ligand and target were studied using a flexible docking method (FlexX). The best scored candidates were docked flexibly, and the interaction between the benzoic acid derivatives and the tyrosinase active site was elucidated in detail. We believe
Quantitative structure-property relationship (QSPR) modeling of drug-loaded polymeric micelles via genetic function approximation.

PubMed

Wu, Wensheng; Zhang, Canyang; Lin, Wenjing; Chen, Quan; Guo, Xindong; Qian, Yu; Zhang, Lijuan

2015-01-01

Self-assembled nano-micelles of amphiphilic polymers represent a novel anticancer drug delivery system. However, their full clinical utilization remains challenging because the quantitative structure-property relationship (QSPR) between the polymer structure and the efficacy of micelles as a drug carrier is poorly understood. Here, we developed a series of QSPR models to account for the drug loading capacity of polymeric micelles using the genetic function approximation (GFA) algorithm. These models were further evaluated by internal and external validation and a Y-randomization test in terms of stability and generalization, yielding an optimization model that is applicable to an expanded materials regime. As confirmed by experimental data, the relationship between microstructure and drug loading capacity can be well-simulated, suggesting that our models are readily applicable to the quantitative evaluation of the drug-loading capacity of polymeric micelles. Our work may offer a pathway to the design of formulation experiments.
Relationship between bicarbonate retention and bone characteristics in broiler chickens.

PubMed

Leslie, M A; Coleman, R A; Moehn, S; Ball, R O; Korver, D R

2006-11-01

Determination of the bicarbonate retention factor (BRF) is an important step during development of the indicator amino acid oxidation technique for use in a new model. A series of 4-h oxidation experiments were performed to determine the BRF of broilers aged 7, 14, 21, 28, 35, and 42 d using 4 birds per age group. A priming dose of 1.2 microCi of NaH(14)CO(3), followed by eight half-hourly doses of 1 microCi of NaH(14)CO(3) were given orally to each of 4 birds per age. The percentage of (14)C dose expired by the bird at a steady state was measured. These birds, as well as 12 additional birds matched for age and BW, were killed, and femur bone mineral density was measured by quantitative computed tomography to determine the relationship between bone development and bicarbonate retention at each age. There was a correlation (r = 0.50; P < 0.05) between total cross-sectional femur bone mineral density and bicarbonate retention at each age. A prediction equation (Y = 6.95 x 10(-2)X - 3.51 x 10(-5)X(2) + 27.58; P < 0.0001, R(2) = 0.79) where Y = bicarbonate retention and X = BW was generated to predict Y as a function of X. Bicarbonate retention values peaked at 28 d, during the stage of the most rapid bone deposition and the highest growth rate. A constant BRF was found from 1,900 to 2,700 g of BW of 35.15 +/- 1.095% (mean +/- SEM). This retention factor will allow the accurate correction of oxidation of (14)C-labeled substrates in broilers of different ages and BW in future indicator amino acid oxidation studies.
Quantitative Structure-Property Relationship (QSPR) Modeling of Drug-Loaded Polymeric Micelles via Genetic Function Approximation

PubMed Central

Lin, Wenjing; Chen, Quan; Guo, Xindong; Qian, Yu; Zhang, Lijuan

2015-01-01

Self-assembled nano-micelles of amphiphilic polymers represent a novel anticancer drug delivery system. However, their full clinical utilization remains challenging because the quantitative structure-property relationship (QSPR) between the polymer structure and the efficacy of micelles as a drug carrier is poorly understood. Here, we developed a series of QSPR models to account for the drug loading capacity of polymeric micelles using the genetic function approximation (GFA) algorithm. These models were further evaluated by internal and external validation and a Y-randomization test in terms of stability and generalization, yielding an optimization model that is applicable to an expanded materials regime. As confirmed by experimental data, the relationship between microstructure and drug loading capacity can be well-simulated, suggesting that our models are readily applicable to the quantitative evaluation of the drug-loading capacity of polymeric micelles. Our work may offer a pathway to the design of formulation experiments. PMID:25780923
Chemical graphs, molecular matrices and topological indices in chemoinformatics and quantitative structure-activity relationships.

PubMed

Ivanciuc, Ovidiu

2013-06-01

Chemical and molecular graphs have fundamental applications in chemoinformatics, quantitative structureproperty relationships (QSPR), quantitative structure-activity relationships (QSAR), virtual screening of chemical libraries, and computational drug design. Chemoinformatics applications of graphs include chemical structure representation and coding, database search and retrieval, and physicochemical property prediction. QSPR, QSAR and virtual screening are based on the structure-property principle, which states that the physicochemical and biological properties of chemical compounds can be predicted from their chemical structure. Such structure-property correlations are usually developed from topological indices and fingerprints computed from the molecular graph and from molecular descriptors computed from the three-dimensional chemical structure. We present here a selection of the most important graph descriptors and topological indices, including molecular matrices, graph spectra, spectral moments, graph polynomials, and vertex topological indices. These graph descriptors are used to define several topological indices based on molecular connectivity, graph distance, reciprocal distance, distance-degree, distance-valency, spectra, polynomials, and information theory concepts. The molecular descriptors and topological indices can be developed with a more general approach, based on molecular graph operators, which define a family of graph indices related by a common formula. Graph descriptors and topological indices for molecules containing heteroatoms and multiple bonds are computed with weighting schemes based on atomic properties, such as the atomic number, covalent radius, or electronegativity. The correlation in QSPR and QSAR models can be improved by optimizing some parameters in the formula of topological indices, as demonstrated for structural descriptors based on atomic connectivity and graph distance.
Determination of quantitative retention-activity relationships between pharmacokinetic parameters and biological effectiveness fingerprints of Salvia miltiorrhiza constituents using biopartitioning and microemulsion high-performance liquid chromatography.

PubMed

Gao, Haoshi; Huang, Hongzhang; Zheng, Aini; Yu, Nuojun; Li, Ning

2017-11-01

In this study, we analyzed danshen (Salvia miltiorrhiza) constituents using biopartitioning and microemulsion high-performance liquid chromatography (MELC). The quantitative retention-activity relationships (QRARs) of the constituents were established to model their pharmacokinetic (PK) parameters and chromatographic retention data, and generate their biological effectiveness fingerprints. A high-performance liquid chromatography (HPLC) method was established to determine the abundance of the extracted danshen constituents, such as sodium danshensu, rosmarinic acid, salvianolic acid B, protocatechuic aldehyde, cryptotanshinone, and tanshinone IIA. And another HPLC protocol was established to determine the abundance of those constituents in rat plasma samples. An experimental model was built in Sprague Dawley (SD) rats, and calculated the corresponding PK parameterst with 3P97 software package. Thirty-five model drugs were selected to test the PK parameter prediction capacities of the various MELC systems and to optimize the chromatographic protocols. QRARs and generated PK fingerprints were established. The test included water/oil-soluble danshen constituents and the prediction capacity of the regression model was validated. The results showed that the model had good predictability. Copyright © 2017. Published by Elsevier B.V.
Quantitative structure-cytotoxicity relationship of phenylpropanoid amides.

PubMed

Shimada, Chiyako; Uesawa, Yoshihiro; Ishihara, Mariko; Kagaya, Hajime; Kanamoto, Taisei; Terakubo, Shigemi; Nakashima, Hideki; Takao, Koichi; Saito, Takayuki; Sugita, Yoshiaki; Sakagami, Hiroshi

2014-07-01

A total of 12 phenylpropanoid amides were subjected to quantitative structure-activity relationship (QSAR) analysis, based on their cytotoxicity, tumor selectivity and anti-HIV activity, in order to investigate on their biological activities. Cytotoxicity against four human oral squamous cell carcinoma (OSCC) cell lines and three human oral normal cells was determined by the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) method. Tumor selectivity was evaluated by the ratio of the mean CC50 (50% cytotoxic concentration) against normal oral cells to that against OSCC cell lines. Anti-HIV activity was evaluated by the ratio of CC50 to EC50 (50% cytoprotective concentration from HIV infection). Physicochemical, structural, and quantum-chemical parameters were calculated based on the conformations optimized by the LowModeMD method followed by density functional theory (DFT) method. Twelve phenylpropanoid amides showed moderate cytotoxicity against both normal and OSCC cell lines. N-Caffeoyl derivatives coupled with vanillylamine and tyramine exhibited relatively higher tumor selectivity. Cytotoxicity against normal cells was correlated with descriptors related to electrostatic interaction such as polar surface area and chemical hardness, whereas cytotoxicity against tumor cells correlated with free energy, surface area and ellipticity. The tumor-selective cytotoxicity correlated with molecular size (surface area) and electrostatic interaction (the maximum electrostatic potential). The molecular size, shape and ability for electrostatic interaction are useful parameters for estimating the tumor selectivity of phenylpropanoid amides. Copyright© 2014 International Institute of Anticancer Research (Dr. John G. Delinassios), All rights reserved.
The Relationship between Administrative Leadership Behaviors and Teacher Retention in Christian Schools

ERIC Educational Resources Information Center

Jones, Deana; Watson, Scott B.

2017-01-01

The purpose of this correlational study was to determine if there is a relationship between the principal's consideration or initiating structure leadership behaviors and teacher retention in the American Association of Christian Schools (AACS). A random sample of 100 teachers from the American Association of Christian Schools participated in the…
Nonparametric regression applied to quantitative structure-activity relationships

PubMed

Constans; Hirst

2000-03-01

Several nonparametric regressors have been applied to modeling quantitative structure-activity relationship (QSAR) data. The simplest regressor, the Nadaraya-Watson, was assessed in a genuine multivariate setting. Other regressors, the local linear and the shifted Nadaraya-Watson, were implemented within additive models--a computationally more expedient approach, better suited for low-density designs. Performances were benchmarked against the nonlinear method of smoothing splines. A linear reference point was provided by multilinear regression (MLR). Variable selection was explored using systematic combinations of different variables and combinations of principal components. For the data set examined, 47 inhibitors of dopamine beta-hydroxylase, the additive nonparametric regressors have greater predictive accuracy (as measured by the mean absolute error of the predictions or the Pearson correlation in cross-validation trails) than MLR. The use of principal components did not improve the performance of the nonparametric regressors over use of the original descriptors, since the original descriptors are not strongly correlated. It remains to be seen if the nonparametric regressors can be successfully coupled with better variable selection and dimensionality reduction in the context of high-dimensional QSARs.

Quantitative structure-cytotoxicity relationship of piperic acid amides.

PubMed

Shimada, Chiyako; Uesawa, Yoshihiro; Ishihara, Mariko; Kagaya, Hajime; Kanamoto, Taisei; Terakubo, Shigemi; Nakashima, Hideki; Takao, Koichi; Miyashiro, Takaki; Sugita, Yoshiaki; Sakagami, Hiroshi

2014-09-01

A total of 12 piperic acid amides, including piperine, were subjected to quantitative structure-activity relationship (QSAR) analysis, based on their cytotoxicity, tumor selectivity and anti-HIV activity, in order to find new biological activities. Cytotoxicity against four human oral squamous cell carcinoma (OSCC) cell lines and three human oral normal cells was determined by the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) method. Tumor selectivity was evaluated by the ratio of the mean 50% cytotoxic concentration (CC50) against normal oral cells to that against OSCC cell lines. Anti-HIV activity was evaluated by the ratio of the CC50 to 50% HIV infection-cytoprotective concentration (EC50). Physicochemical, structural, and quantum-chemical parameters were calculated based on the conformations optimized by LowModeMD method followed by density functional theory method. All compounds showed low-to-moderate tumor selectivity, but no anti-HIV activity. N-Piperoyldopamine ( 8: ) which has a catechol moiety, showed the highest tumor selectivity, possibly due to its unique molecular shape and electrostatic interaction, especially its largest partial equalization of orbital electronegativities and vsurf descriptors. The present study suggests that molecular shape and ability for electrostatic interaction are useful parameters for estimating the tumor selectivity of piperic acid amides. Copyright© 2014 International Institute of Anticancer Research (Dr. John G. Delinassios), All rights reserved.
Quantitative structure property relationships for the adsorption of pharmaceuticals onto activated carbon.

PubMed

Dickenson, E R V; Drewes, J E

2010-01-01

Isotherms were determined for the adsorption of five pharmaceutical residues, primidone, carbamazepine, ibuprofen, naproxen and diclofenac, to Calgon Filtrasorb 300 powdered activated carbon (PAC). The sorption behavior was examined in ultra-pure and wastewater effluent organic matter (EfOM) matrices, where more sorption was observed in the ultra-pure water for PAC doses greater than 10 mg/L suggesting the presence of EfOM hinders the sorption of the pharmaceuticals to the PAC. Adsorption behaviors were described by the Freundlich isotherm model. Quantitative structure property relationships (QSPRs) in the form of polyparameter linear solvation energy relationships were developed for simulating the Freundlich adsorption capacity in both ultra-pure and EfOM matrices. The significant 3D-based descriptors for the QSPRs were the molar volume, polarizability and hydrogen-bond donor parameters.
Application of perfluorinated acids as ion-pairing reagents for reversed-phase chromatography and retention-hydrophobicity relationships studies of selected beta-blockers.

PubMed

Flieger, J

2010-01-22

The addition of the homologous series of perfluorinated acids-trifluoroacetic acid (TFAA), pentafluoropropionic acid (PFPA), heptafluorobutyric acid (HFBA) to mobile phases for reversed-phase high-performance liquid chromatography (RP-HPLC) of beta-blockers was tested. Acidic modifiers were responsible for acidification of mobile phase (pH 3) ensuring the protonation of the beta-blockers and further ion pairs creation. The effect of the type and concentration of mobile phase additives on retention parameters, the efficiency of the peaks, their symmetry and separation selectivity of the beta-blockers mixture were all studied. It appeared that at increasing acid concentration, the retention factor, for all compounds investigated, increased to varying degrees. It should be stressed that the presence of acids more significantly affected the retention of the most hydrophobic beta-blockers. Differences in hydrophobicity of drugs can be maximized through variation of the hydrophobicity of additives. Thus, the relative increase in the retention depends on either concentration and hydrophobicity of the anionic mobile phase additive or hydrophobicity of analytes. According to QSRR (quantitative structure retention relationship) methodology, chromatographic lipophilicity parameters: isocratic log k and log k(w) values (extrapolated retention to pure water) were correlated with the molecular (log P(o/w)) and apparent (log P(app)) octanol-water partition coefficients obtained experimentally by countercurrent chromatography (CCC) or predicted by Pallas software. The obtained, satisfactory retention-hydrophobicity correlations indicate that, in the case of the basic drugs examined in RP-HPLC systems modified with perfluorinated acids, the retention is mainly governed by their hydrophobicity. Copyright 2009 Elsevier B.V. All rights reserved.
Quantitative studies on structure-DPPH• scavenging activity relationships of food phenolic acids.

PubMed

Jing, Pu; Zhao, Shu-Juan; Jian, Wen-Jie; Qian, Bing-Jun; Dong, Ying; Pang, Jie

2012-11-01

Phenolic acids are potent antioxidants, yet the quantitative structure-activity relationships of phenolic acids remain unclear. The purpose of this study was to establish 3D-QSAR models able to predict phenolic acids with high DPPH• scavenging activity and understand their structure-activity relationships. The model has been established by using a training set of compounds with cross-validated q2 = 0.638/0.855, non-cross-validated r2 = 0.984/0.986, standard error of estimate = 0.236/0.216, and F = 139.126/208.320 for the best CoMFA/CoMSIA models. The predictive ability of the models was validated with the correlation coefficient r2(pred) = 0.971/0.996 (>0.6) for each model. Additionally, the contour map results suggested that structural characteristics of phenolics acids favorable for the high DPPH• scavenging activity might include: (1) bulky and/or electron-donating substituent groups on the phenol ring; (2) electron-donating groups at the meta-position and/or hydrophobic groups at the meta-/ortho-position; (3) hydrogen-bond donor/electron-donating groups at the ortho-position. The results have been confirmed based on structural analyses of phenolic acids and their DPPH• scavenging data from eight recent publications. The findings may provide deeper insight into the antioxidant mechanisms and provide useful information for selecting phenolic acids for free radical scavenging properties.
Improving Student Retention and Performance in Quantitative Courses Using Clickers

ERIC Educational Resources Information Center

Liu, Wallace C.; Stengel, Donald N.

2011-01-01

Clickers offer instructors of mathematics-related courses an opportunity to involve students actively in class sessions while diminishing the embarrassment of being wrong. This paper reports on the use of clickers in two university-level courses in quantitative analysis and business statistics. Results for student retention and examination…
Investigation on Quantitative Structure Activity Relationships of a Series of Inducible Nitric Oxide.

PubMed

Sharma, Mukesh C; Sharma, S

2016-12-01

A series of 2-dihydro-4-quinazolin with potent highly selective inhibitors of inducible nitric oxide synthase activities was subjected to quantitative structure activity relationships (QSAR) analysis. Statistically significant equations with high correlation coefficient (r 2 = 0.8219) were developed. The k-nearest neighbor model has showed good cross-validated correlation coefficient and external validation values of 0.7866 and 0.7133, respectively. The selected electrostatic field descriptors the presence of blue ball around R1 and R4 in the quinazolinamine moiety showed electronegative groups favorable for nitric oxide synthase activity. The QSAR models may lead to the structural requirements of inducible nitric oxide compounds and help in the design of new compounds.
Quantitative structure-activity relationship (QSAR) for insecticides: development of predictive in vivo insecticide activity models.

PubMed

Naik, P K; Singh, T; Singh, H

2009-07-01

Quantitative structure-activity relationship (QSAR) analyses were performed independently on data sets belonging to two groups of insecticides, namely the organophosphates and carbamates. Several types of descriptors including topological, spatial, thermodynamic, information content, lead likeness and E-state indices were used to derive quantitative relationships between insecticide activities and structural properties of chemicals. A systematic search approach based on missing value, zero value, simple correlation and multi-collinearity tests as well as the use of a genetic algorithm allowed the optimal selection of the descriptors used to generate the models. The QSAR models developed for both organophosphate and carbamate groups revealed good predictability with r(2) values of 0.949 and 0.838 as well as [image omitted] values of 0.890 and 0.765, respectively. In addition, a linear correlation was observed between the predicted and experimental LD(50) values for the test set data with r(2) of 0.871 and 0.788 for both the organophosphate and carbamate groups, indicating that the prediction accuracy of the QSAR models was acceptable. The models were also tested successfully from external validation criteria. QSAR models developed in this study should help further design of novel potent insecticides.
ESTIMATION OF MICROBIAL REDUCTIVE TRANSFORMATION RATES FOR CHLORINATED BENZENES AND PHENOLS USING A QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIP APPROACH

EPA Science Inventory

A set of literature data was used to derive several quantitative structure-activity relationships (QSARs) to predict the rate constants for the microbial reductive dehalogenation of chlorinated aromatics. Dechlorination rate constants for 25 chloroaromatics were corrected for th...
Toxicity challenges in environmental chemicals: Prediction of human plasma protein binding through quantitative structure-activity relationship (QSAR) models

EPA Science Inventory

The present study explores the merit of utilizing available pharmaceutical data to construct a quantitative structure-activity relationship (QSAR) for prediction of the fraction of a chemical unbound to plasma protein (Fub) in environmentally relevant compounds. Independent model...
Faculty Personality: A Factor of Student Retention

ERIC Educational Resources Information Center

Shaw, Cassandra S.; Wu, Xiaodong; Irwin, Kathleen C.; Patrizi, L. A. Chad

2016-01-01

The purpose of this study was to determine the relationship between student retention and faculty personality as it was hypothesized that faculty personality has an effect on student retention. The methodology adopted for this study was quantitative and in two parts 1) using linear regression models to examine the impact or causality of faculty…
Designing a Quantitative Structure-Activity Relationship for the ...

EPA Pesticide Factsheets

Toxicokinetic models serve a vital role in risk assessment by bridging the gap between chemical exposure and potentially toxic endpoints. While intrinsic metabolic clearance rates have a strong impact on toxicokinetics, limited data is available for environmentally relevant chemicals including nearly 8000 chemicals tested for in vitro bioactivity in the Tox21 program. To address this gap, a quantitative structure-activity relationship (QSAR) for intrinsic metabolic clearance rate was developed to offer reliable in silico predictions for a diverse array of chemicals. Models were constructed with curated in vitro assay data for both pharmaceutical-like chemicals (ChEMBL database) and environmentally relevant chemicals (ToxCast screening) from human liver microsomes (2176 from ChEMBL) and human hepatocytes (757 from ChEMBL and 332 from ToxCast). Due to variability in the experimental data, a binned approach was utilized to classify metabolic rates. Machine learning algorithms, such as random forest and k-nearest neighbor, were coupled with open source molecular descriptors and fingerprints to provide reasonable estimates of intrinsic metabolic clearance rates. Applicability domains defined the optimal chemical space for predictions, which covered environmental chemicals well. A reduced set of informative descriptors (including relative charge and lipophilicity) and a mixed training set of pharmaceuticals and environmentally relevant chemicals provided the best intr
Quantitative Structure-Cytotoxicity Relationship of Cinnamic Acid Phenetyl Esters.

PubMed

Uesawa, Yoshihiro; Sakagami, Hiroshi; Okudaira, Noriyuki; Toda, Kazuhiro; Takao, Koichi; Kagaya, Hajime; Sugita, Yoshiaki

2018-02-01

Many phenolic acid phenethyl esters possess diverse biological effects including antioxidant, cytoprotective, anti-inflammation and anti-tumor activities. However, most previous antitumor studies have not considered the cytotoxicity against normal cells. Ten cinnamic acid phenetyl esters were subjected to quantitative structure-activity relationship (QSAR) analysis, based on their cytotoxicity and tumor-specificity, in order to find their new biological activities. Cytotoxicity against four human oral squamous cell carcinoma cell lines and three oral normal mesenchymal cells was determined by the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) method. Tumor specificity (TS) was evaluated by the ratio of the mean 50% cytotoxic concentration (CC 50 ) against normal oral cells to that against human oral squamous cell carcinoma cell lines. Potency-selectivity expression (PSE) value was calculated by dividing the TS value by CC 50 against tumor cells. Apoptosis markers were detected by western blot analysis. Physicochemical, structural and quantum-chemical parameters were calculated based on the conformations optimized by force-field minimization. Western blot analysis demonstrated that [ 9 ] stimulated the cleavage of caspase-3, suggesting the induction of apoptosis. QSAR analysis demonstrated that TS values were correlated with shape, size and ionization potential. Chemical modification of the lead compound may be a potential choice for designing a new type of anticancer drugs. Copyright© 2018, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.
Quantitative structure-activity relationship: promising advances in drug discovery platforms.

PubMed

Wang, Tao; Wu, Mian-Bin; Lin, Jian-Ping; Yang, Li-Rong

2015-12-01

Quantitative structure-activity relationship (QSAR) modeling is one of the most popular computer-aided tools employed in medicinal chemistry for drug discovery and lead optimization. It is especially powerful in the absence of 3D structures of specific drug targets. QSAR methods have been shown to draw public attention since they were first introduced. In this review, the authors provide a brief discussion of the basic principles of QSAR, model development and model validation. They also highlight the current applications of QSAR in different fields, particularly in virtual screening, rational drug design and multi-target QSAR. Finally, in view of recent controversies, the authors detail the challenges faced by QSAR modeling and the relevant solutions. The aim of this review is to show how QSAR modeling can be applied in novel drug discovery, design and lead optimization. QSAR should intentionally be used as a powerful tool for fragment-based drug design platforms in the field of drug discovery and design. Although there have been an increasing number of experimentally determined protein structures in recent years, a great number of protein structures cannot be easily obtained (i.e., membrane transport proteins and G-protein coupled receptors). Fragment-based drug discovery, such as QSAR, could be applied further and have a significant role in dealing with these problems. Moreover, along with the development of computer software and hardware, it is believed that QSAR will be increasingly important.
Quantitative description on structure-property relationships of Li-ion battery materials for high-throughput computations

NASA Astrophysics Data System (ADS)

Wang, Youwei; Zhang, Wenqing; Chen, Lidong; Shi, Siqi; Liu, Jianjun

2017-12-01

Li-ion batteries are a key technology for addressing the global challenge of clean renewable energy and environment pollution. Their contemporary applications, for portable electronic devices, electric vehicles, and large-scale power grids, stimulate the development of high-performance battery materials with high energy density, high power, good safety, and long lifetime. High-throughput calculations provide a practical strategy to discover new battery materials and optimize currently known material performances. Most cathode materials screened by the previous high-throughput calculations cannot meet the requirement of practical applications because only capacity, voltage and volume change of bulk were considered. It is important to include more structure-property relationships, such as point defects, surface and interface, doping and metal-mixture and nanosize effects, in high-throughput calculations. In this review, we established quantitative description of structure-property relationships in Li-ion battery materials by the intrinsic bulk parameters, which can be applied in future high-throughput calculations to screen Li-ion battery materials. Based on these parameterized structure-property relationships, a possible high-throughput computational screening flow path is proposed to obtain high-performance battery materials.
Quantitative description on structure-property relationships of Li-ion battery materials for high-throughput computations.

PubMed

Wang, Youwei; Zhang, Wenqing; Chen, Lidong; Shi, Siqi; Liu, Jianjun

2017-01-01

Li-ion batteries are a key technology for addressing the global challenge of clean renewable energy and environment pollution. Their contemporary applications, for portable electronic devices, electric vehicles, and large-scale power grids, stimulate the development of high-performance battery materials with high energy density, high power, good safety, and long lifetime. High-throughput calculations provide a practical strategy to discover new battery materials and optimize currently known material performances. Most cathode materials screened by the previous high-throughput calculations cannot meet the requirement of practical applications because only capacity, voltage and volume change of bulk were considered. It is important to include more structure-property relationships, such as point defects, surface and interface, doping and metal-mixture and nanosize effects, in high-throughput calculations. In this review, we established quantitative description of structure-property relationships in Li-ion battery materials by the intrinsic bulk parameters, which can be applied in future high-throughput calculations to screen Li-ion battery materials. Based on these parameterized structure-property relationships, a possible high-throughput computational screening flow path is proposed to obtain high-performance battery materials.
A Short Review of the Generation of Molecular Descriptors and Their Applications in Quantitative Structure Property/Activity Relationships.

PubMed

Sahoo, Sagarika; Adhikari, Chandana; Kuanar, Minati; Mishra, Bijay K

2016-01-01

Synthesis of organic compounds with specific biological activity or physicochemical characteristics needs a thorough analysis of the enumerable data set obtained from literature. Quantitative structure property/activity relationships have made it simple by predicting the structure of the compound with any optimized activity. For that there is a paramount data set of molecular descriptors (MD). This review is a survey on the generation of the molecular descriptors and its probable applications in QSP/AR. Literatures have been collected from a wide class of research journals, citable web reports, seminar proceedings and books. The MDs were classified according to their generation. The applications of the MDs on the QSP/AR have also been reported in this review. The MDs can be classified into experimental and theoretical types, having a sub classification of the later into structural and quantum chemical descriptors. The structural parameters are derived from molecular graphs or topology of the molecules. Even the pixel of the molecular image can be used as molecular descriptor. In QSPR studies the physicochemical properties include boiling point, heat capacity, density, refractive index, molar volume, surface tension, heat of formation, octanol-water partition coefficient, solubility, chromatographic retention indices etc. Among biological activities toxicity, antimalarial activity, sensory irritant, potencies of local anesthetic, tadpole narcosis, antifungal activity, enzyme inhibiting activity are some important parameters in the QSAR studies. The classification of the MDs is mostly generic in nature. The application of the MDs in QSP/AR also has a generic link. Experimental MDs are more suitable in correlation analysis than the theoretical ones but are more expensive for generation. In advent of sophisticated computational tools and experimental design proliferation of MDs is inevitable, but for a highly optimized MD, studies on generation of MD is an unending
Comparative Analysis of Predictive Models for Liver Toxicity Using ToxCast Assays and Quantitative Structure-Activity Relationships (MCBIOS)

EPA Science Inventory

Comparative Analysis of Predictive Models for Liver Toxicity Using ToxCast Assays and Quantitative Structure-Activity Relationships Jie Liu1,2, Richard Judson1, Matthew T. Martin1, Huixiao Hong3, Imran Shah1 1National Center for Computational Toxicology (NCCT), US EPA, RTP, NC...
Molecular basis of quantitative structure-properties relationships (QSPR): a quantum similarity approach.

PubMed

Ponec, R; Amat, L; Carbó-Dorca, R

1999-05-01

Since the dawn of quantitative structure-properties relationships (QSPR), empirical parameters related to structural, electronic and hydrophobic molecular properties have been used as molecular descriptors to determine such relationships. Among all these parameters, Hammett sigma constants and the logarithm of the octanol-water partition coefficient, log P, have been massively employed in QSPR studies. In the present paper, a new molecular descriptor, based on quantum similarity measures (QSM), is proposed as a general substitute of these empirical parameters. This work continues previous analyses related to the use of QSM to QSPR, introducing molecular quantum self-similarity measures (MQS-SM) as a single working parameter in some cases. The use of MQS-SM as a molecular descriptor is first confirmed from the correlation with the aforementioned empirical parameters. The Hammett equation has been examined using MQS-SM for a series of substituted carboxylic acids. Then, for a series of aliphatic alcohols and acetic acid esters, log P values have been correlated with the self-similarity measure between density functions in water and octanol of a given molecule. And finally, some examples and applications of MQS-SM to determine QSAR are presented. In all studied cases MQS-SM appeared to be excellent molecular descriptors usable in general QSPR applications of chemical interest.
Molecular basis of quantitative structure-properties relationships (QSPR): A quantum similarity approach

NASA Astrophysics Data System (ADS)

Ponec, Robert; Amat, Lluís; Carbó-dorca, Ramon

1999-05-01

Since the dawn of quantitative structure-properties relationships (QSPR), empirical parameters related to structural, electronic and hydrophobic molecular properties have been used as molecular descriptors to determine such relationships. Among all these parameters, Hammett σ constants and the logarithm of the octanol- water partition coefficient, log P, have been massively employed in QSPR studies. In the present paper, a new molecular descriptor, based on quantum similarity measures (QSM), is proposed as a general substitute of these empirical parameters. This work continues previous analyses related to the use of QSM to QSPR, introducing molecular quantum self-similarity measures (MQS-SM) as a single working parameter in some cases. The use of MQS-SM as a molecular descriptor is first confirmed from the correlation with the aforementioned empirical parameters. The Hammett equation has been examined using MQS-SM for a series of substituted carboxylic acids. Then, for a series of aliphatic alcohols and acetic acid esters, log P values have been correlated with the self-similarity measure between density functions in water and octanol of a given molecule. And finally, some examples and applications of MQS-SM to determine QSAR are presented. In all studied cases MQS-SM appeared to be excellent molecular descriptors usable in general QSPR applications of chemical interest.
Molecule kernels: a descriptor- and alignment-free quantitative structure-activity relationship approach.

PubMed

Mohr, Johannes A; Jain, Brijnesh J; Obermayer, Klaus

2008-09-01

Quantitative structure activity relationship (QSAR) analysis is traditionally based on extracting a set of molecular descriptors and using them to build a predictive model. In this work, we propose a QSAR approach based directly on the similarity between the 3D structures of a set of molecules measured by a so-called molecule kernel, which is independent of the spatial prealignment of the compounds. Predictors can be build using the molecule kernel in conjunction with the potential support vector machine (P-SVM), a recently proposed machine learning method for dyadic data. The resulting models make direct use of the structural similarities between the compounds in the test set and a subset of the training set and do not require an explicit descriptor construction. We evaluated the predictive performance of the proposed method on one classification and four regression QSAR datasets and compared its results to the results reported in the literature for several state-of-the-art descriptor-based and 3D QSAR approaches. In this comparison, the proposed molecule kernel method performed better than the other QSAR methods.

Quantitative structure-activity relationship of organosulphur compounds as soybean 15-lipoxygenase inhibitors using CoMFA and CoMSIA.

PubMed

Caballero, Julio; Fernández, Michael; Coll, Deysma

2010-12-01

Three-dimensional quantitative structure-activity relationship studies were carried out on a series of 28 organosulphur compounds as 15-lipoxygenase inhibitors using comparative molecular field analysis and comparative molecular similarity indices analysis. Quantitative information on structure-activity relationships is provided for further rational development and direction of selective synthesis. All models were carried out over a training set including 22 compounds. The best comparative molecular field analysis model only included steric field and had a good Q² = 0.789. Comparative molecular similarity indices analysis overcame the comparative molecular field analysis results: the best comparative molecular similarity indices analysis model also only included steric field and had a Q² = 0.894. In addition, this model predicted adequately the compounds contained in the test set. Furthermore, plots of steric comparative molecular similarity indices analysis field allowed conclusions to be drawn for the choice of suitable inhibitors. In this sense, our model should prove useful in future 15-lipoxygenase inhibitor design studies. © 2010 John Wiley & Sons A/S.
Aquatic toxicity of acrylates and methacrylates: quantitative structure-activity relationships based on Kow and LC50

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

Reinert, K.H.

1987-12-01

Recent EPA scrutiny of acrylate and methacrylate monomers has resulted in restrictive consent orders and Significant New Use Rules under the Toxic Substances Control Act, based on structure-activity relationships using mouse skin painting studies. The concern is centered on human health issues regarding worker and consumer exposure. Environmental issues, such as aquatic toxicity, are still of concern. Understanding the relationships and environmental risks to aquatic organisms may improve the understanding of the potential risks to human health. This study evaluates the quantitative structure-activity relationships from measured log Kow's and log LC50's for Pimephales promelas (fathead minnow) and Carassius auratus (goldfish).more » Scientific support of the current regulations is also addressed. Two monomer classes were designated: acrylates and methacrylates. Spearman rank correlation and linear regression were run. Based on this study, an ecotoxicological difference exists between acrylates and methacrylates. Regulatory activities and scientific study should reflect this difference.« less
Relationship of Personality Traits to Student Retention

ERIC Educational Resources Information Center

Liang, John Paul

2010-01-01

Carl Jung's theory of psychological types has been the basis for the development of personality categorization, including tests such as Myers-Briggs Type Indicator (MBTI). This study analyzed the extent of the relationship between MBTI and Tinto (1993) retention factors that influence Oriental medicine students' choice of staying or dropping out…
Quantitative structure-activity relationships for organophosphates binding to acetylcholinesterase.

PubMed

Ruark, Christopher D; Hack, C Eric; Robinson, Peter J; Anderson, Paul E; Gearhart, Jeffery M

2013-02-01

Organophosphates are a group of pesticides and chemical warfare nerve agents that inhibit acetylcholinesterase, the enzyme responsible for hydrolysis of the excitatory neurotransmitter acetylcholine. Numerous structural variants exist for this chemical class, and data regarding their toxicity can be difficult to obtain in a timely fashion. At the same time, their use as pesticides and military weapons is widespread, which presents a major concern and challenge in evaluating human toxicity. To address this concern, a quantitative structure-activity relationship (QSAR) was developed to predict pentavalent organophosphate oxon human acetylcholinesterase bimolecular rate constants. A database of 278 three-dimensional structures and their bimolecular rates was developed from 15 peer-reviewed publications. A database of simplified molecular input line entry notations and their respective acetylcholinesterase bimolecular rate constants are listed in Supplementary Material, Table I. The database was quite diverse, spanning 7 log units of activity. In order to describe their structure, 675 molecular descriptors were calculated using AMPAC 8.0 and CODESSA 2.7.10. Orthogonal projection to latent structures regression, bootstrap leave-random-many-out cross-validation and y-randomization were used to develop an externally validated consensus QSAR model. The domain of applicability was assessed by the William's plot. Six external compounds were outside the warning leverage indicating potential model extrapolation. A number of compounds had residuals >2 or <-2, indicating potential outliers or activity cliffs. The results show that the HOMO-LUMO energy gap contributed most significantly to the binding affinity. A mean training R (2) of 0.80, a mean test set R (2) of 0.76 and a consensus external test set R (2) of 0.66 were achieved using the QSAR. The training and external test set RMSE values were found to be 0.76 and 0.88. The results suggest that this QSAR model can be used in
Design, synthesis and exploring the quantitative structure-activity relationship of some antioxidant flavonoid analogues.

PubMed

Das, Sreeparna; Mitra, Indrani; Batuta, Shaikh; Niharul Alam, Md; Roy, Kunal; Begum, Naznin Ara

2014-11-01

A series of flavonoid analogues were synthesized and screened for the in vitro antioxidant activity through their ability to quench 1,1-diphenyl-2-picryl hydrazyl (DPPH) radical. The activity of these compounds, measured in comparison to the well-known standard antioxidants (29-32), their precursors (38-42) and other bioactive moieties (38-42) resembling partially the flavone skeleton was analyzed further to develop Quantitative Structure-Activity Relationship (QSAR) models using the Genetic Function Approximation (GFA) technique. Based on the essential structural requirements predicted by the QSAR models, some analogues were designed, synthesized and tested for activity. The predicted and experimental activities of these compounds were well correlated. Flavone analogue 20 was found to be the most potent antioxidant. Copyright © 2014 Elsevier Ltd. All rights reserved.
3D-quantitative structure-activity relationship studies on benzothiadiazepine hydroxamates as inhibitors of tumor necrosis factor-alpha converting enzyme.

PubMed

Murumkar, Prashant R; Giridhar, Rajani; Yadav, Mange Ram

2008-04-01

A set of 29 benzothiadiazepine hydroxamates having selective tumor necrosis factor-alpha converting enzyme inhibitory activity were used to compare the quality and predictive power of 3D-quantitative structure-activity relationship, comparative molecular field analysis, and comparative molecular similarity indices models for the atom-based, centroid/atom-based, data-based, and docked conformer-based alignment. Removal of two outliers from the initial training set of molecules improved the predictivity of models. Among the 3D-quantitative structure-activity relationship models developed using the above four alignments, the database alignment provided the optimal predictive comparative molecular field analysis model for the training set with cross-validated r(2) (q(2)) = 0.510, non-cross-validated r(2) = 0.972, standard error of estimates (s) = 0.098, and F = 215.44 and the optimal comparative molecular similarity indices model with cross-validated r(2) (q(2)) = 0.556, non-cross-validated r(2) = 0.946, standard error of estimates (s) = 0.163, and F = 99.785. These models also showed the best test set prediction for six compounds with predictive r(2) values of 0.460 and 0.535, respectively. The contour maps obtained from 3D-quantitative structure-activity relationship studies were appraised for activity trends for the molecules analyzed. The comparative molecular similarity indices models exhibited good external predictivity as compared with that of comparative molecular field analysis models. The data generated from the present study helped us to further design and report some novel and potent tumor necrosis factor-alpha converting enzyme inhibitors.
The Relationship between Principal Support and Teacher Retention in Hard to Staff Schools

ERIC Educational Resources Information Center

Hughes, Amy L.

2012-01-01

This dissertation examines the relationship between principal support and retention of teachers in hard to staff schools. The purpose of this study was to, (a) to determine the relationship between teacher retention and principal support, (b) to examine the perception of support between teachers and principals and how these perceptions affect…
Quantitative structure-activity relationship studies of threo-methylphenidate analogs.

PubMed

Misra, Milind; Shi, Qing; Ye, Xiaocong; Gruszecka-Kowalik, Ewa; Bu, Wei; Liu, Zhanzhu; Schweri, Margaret M; Deutsch, Howard M; Venanzi, Carol A

2010-10-15

Complementary two-dimensional (2D) and three-dimensional (3D) Quantitative Structure-Activity Relationship (QSAR) techniques were used to derive a preliminary model for the dopamine transporter (DAT) binding affinity of 80 racemic threo-methylphenidate (MP) analogs. A novel approach based on using the atom-level E-state indices of the 14 common scaffold atoms in a sphere exclusion protocol was used to identify a test set for 2D- and 3D-QSAR model validation. Comparative Molecular Field Analysis (CoMFA) contour maps based on the structure-activity data of the training set indicate that the 2' position of the phenyl ring cannot tolerate much steric bulk and that addition of electron-withdrawing groups to the 3' or 4' positions of the phenyl ring leads to improved DAT binding affinity. In particular, the optimal substituents were found to be those whose bulk is mainly in the plane of the phenyl ring. Substituents with significant bulk above or below the plane of the ring led to decreased binding affinity. Suggested alterations to be explored in the design of new compounds are the placement at the 3' and 4' position of the phenyl ring of electron-withdrawing groups that lie chiefly in the plane of the ring, for example, halogen substituents on the 3',4'-benzo analog, 79. A complementary 2D-QSAR approach-partial least squares analysis using a reduced set of Molconn-Z descriptors-supports the CoMFA structure-activity interpretation that phenyl ring substitution is a major determinant of DAT binding affinity. The potential usefulness of the CoMFA models was demonstrated by the prediction of the binding affinity of methyl 2-(naphthalen-1-yl)-2-(piperidin-2-yl)acetate, an analog not in the original data set, to be in good agreement with the experimental value. Copyright © 2010 Elsevier Ltd. All rights reserved.
An orientation sensitive approach in biomolecule interaction quantitative structure-activity relationship modeling and its application in ion-exchange chromatography.

PubMed

Kittelmann, Jörg; Lang, Katharina M H; Ottens, Marcel; Hubbuch, Jürgen

2017-01-27

Quantitative structure-activity relationship (QSAR) modeling for prediction of biomolecule parameters has become an established technique in chromatographic purification process design. Unfortunately available descriptor sets fail to describe the orientation of biomolecules and the effects of ionic strength in the mobile phase on the interaction with the stationary phase. The literature describes several special descriptors used for chromatographic retention modeling, all of these do not describe the screening of electrostatic potential by the mobile phase in use. In this work we introduce two new approaches of descriptor calculations, namely surface patches and plane projection, which capture an oriented binding to charged surfaces and steric hindrance of the interaction with chromatographic ligands with regard to electrostatic potential screening by mobile phase ions. We present the use of the developed descriptor sets for predictive modeling of Langmuir isotherms for proteins at different pH values between pH 5 and 10 and varying ionic strength in the range of 10-100mM. The resulting model has a high correlation of calculated descriptors and experimental results, with a coefficient of determination of 0.82 and a predictive coefficient of determination of 0.92 for unknown molecular structures and conditions. The agreement of calculated molecular interaction orientations with both, experimental results as well as molecular dynamic simulations from literature is shown. The developed descriptors provide the means for improved QSAR models of chromatographic processes, as they reflect the complex interactions of biomolecules with chromatographic phases. Copyright © 2016 Elsevier B.V. All rights reserved.
Toxicity of ionic liquids: database and prediction via quantitative structure-activity relationship method.

PubMed

Zhao, Yongsheng; Zhao, Jihong; Huang, Ying; Zhou, Qing; Zhang, Xiangping; Zhang, Suojiang

2014-08-15

A comprehensive database on toxicity of ionic liquids (ILs) is established. The database includes over 4000 pieces of data. Based on the database, the relationship between IL's structure and its toxicity has been analyzed qualitatively. Furthermore, Quantitative Structure-Activity relationships (QSAR) model is conducted to predict the toxicities (EC50 values) of various ILs toward the Leukemia rat cell line IPC-81. Four parameters selected by the heuristic method (HM) are used to perform the studies of multiple linear regression (MLR) and support vector machine (SVM). The squared correlation coefficient (R(2)) and the root mean square error (RMSE) of training sets by two QSAR models are 0.918 and 0.959, 0.258 and 0.179, respectively. The prediction R(2) and RMSE of QSAR test sets by MLR model are 0.892 and 0.329, by SVM model are 0.958 and 0.234, respectively. The nonlinear model developed by SVM algorithm is much outperformed MLR, which indicates that SVM model is more reliable in the prediction of toxicity of ILs. This study shows that increasing the relative number of O atoms of molecules leads to decrease in the toxicity of ILs. Copyright © 2014 Elsevier B.V. All rights reserved.
Synthesis and quantitative structure-antifungal activity relationships of clovane derivatives against Botrytis cinerea.

PubMed

Saiz-Urra, Liane; Racero, Juan C; Macías-Sáchez, Antonio J; Hernández-Galán, Rosario; Hanson, James R; Perez-Gonzalez, Maykel; Collado, Isidro G

2009-03-25

Twenty-three clovane derivatives, nine described here for the first time, bearing substituents on carbon C-2, have been synthesized and evaluated for their in vitro antifungal activity against the phytopathogenic fungus Botrytis cinerea. The results showed that compounds 9, 14, 16, and 18 bearing nitrogen atoms in the chain attached at C-2 displayed potent antifungal activity, whereas mercapto derivatives 13, 19, and 22 displayed low activity. The antifungal activity showed a clear structure-activity relationship (SAR) trend, which confirmed the importance of the nature of the C-2 chain on the antifungal activity. On the basis of these observations, the metabolism of compounds 8 and 14 by the fungus B. cinerea, and the metabolism of other clovanes by this fungus, described previously, a pro-drug action mechanism for 2-alkoxyclovane compounds is proposed. Quantitative structure-activity relationship (QSAR) studies were performed to rationalize the results and to suggest further optimization, using a topological sub-structural molecular design (TOPS-MODE) approach. The model displayed good fit and predictive capability, describing 85.5% of the experimental variance, with a standard deviation of 9.502 and yielding high values of cross-validation determination coefficients (q2CV-LOO = 0.784 and q2boot = 0.673). The most significant variables were the spectral moments weighted by bond dipole moment (Dip), hydrophobicity (Hyd), and the combined dipolarity/polarizability Abraham molecular descriptor (Ab-pi2H).
Improving quantitative structure-activity relationship models using Artificial Neural Networks trained with dropout.

PubMed

Mendenhall, Jeffrey; Meiler, Jens

2016-02-01

Dropout is an Artificial Neural Network (ANN) training technique that has been shown to improve ANN performance across canonical machine learning (ML) datasets. Quantitative Structure Activity Relationship (QSAR) datasets used to relate chemical structure to biological activity in Ligand-Based Computer-Aided Drug Discovery pose unique challenges for ML techniques, such as heavily biased dataset composition, and relatively large number of descriptors relative to the number of actives. To test the hypothesis that dropout also improves QSAR ANNs, we conduct a benchmark on nine large QSAR datasets. Use of dropout improved both enrichment false positive rate and log-scaled area under the receiver-operating characteristic curve (logAUC) by 22-46 % over conventional ANN implementations. Optimal dropout rates are found to be a function of the signal-to-noise ratio of the descriptor set, and relatively independent of the dataset. Dropout ANNs with 2D and 3D autocorrelation descriptors outperform conventional ANNs as well as optimized fingerprint similarity search methods.
Improving Quantitative Structure-Activity Relationship Models using Artificial Neural Networks Trained with Dropout

PubMed Central

Mendenhall, Jeffrey; Meiler, Jens

2016-01-01

Dropout is an Artificial Neural Network (ANN) training technique that has been shown to improve ANN performance across canonical machine learning (ML) datasets. Quantitative Structure Activity Relationship (QSAR) datasets used to relate chemical structure to biological activity in Ligand-Based Computer-Aided Drug Discovery (LB-CADD) pose unique challenges for ML techniques, such as heavily biased dataset composition, and relatively large number of descriptors relative to the number of actives. To test the hypothesis that dropout also improves QSAR ANNs, we conduct a benchmark on nine large QSAR datasets. Use of dropout improved both Enrichment false positive rate (FPR) and log-scaled area under the receiver-operating characteristic curve (logAUC) by 22–46% over conventional ANN implementations. Optimal dropout rates are found to be a function of the signal-to-noise ratio of the descriptor set, and relatively independent of the dataset. Dropout ANNs with 2D and 3D autocorrelation descriptors outperform conventional ANNs as well as optimized fingerprint similarity search methods. PMID:26830599
Boiling points of halogenated aliphatic compounds: a quantitative structure-property relationship for prediction and validation.

PubMed

Oberg, Tomas

2004-01-01

Halogenated aliphatic compounds have many technical uses, but substances within this group are also ubiquitous environmental pollutants that can affect the ozone layer and contribute to global warming. The establishment of quantitative structure-property relationships is of interest not only to fill in gaps in the available database but also to validate experimental data already acquired. The three-dimensional structures of 240 compounds were modeled with molecular mechanics prior to the generation of empirical descriptors. Two bilinear projection methods, principal component analysis (PCA) and partial-least-squares regression (PLSR), were used to identify outliers. PLSR was subsequently used to build a multivariate calibration model by extracting the latent variables that describe most of the covariation between the molecular structure and the boiling point. Boiling points were also estimated with an extension of the group contribution method of Stein and Brown.
Quantitative structure-activity relationships of selective antagonists of glucagon receptor using QuaSAR descriptors.

PubMed

Manoj Kumar, Palanivelu; Karthikeyan, Chandrabose; Hari Narayana Moorthy, Narayana Subbiah; Trivedi, Piyush

2006-11-01

In the present paper, quantitative structure activity relationship (QSAR) approach was applied to understand the affinity and selectivity of a novel series of triaryl imidazole derivatives towards glucagon receptor. Statistically significant and highly predictive QSARs were derived for glucagon receptor inhibition by triaryl imidazoles using QuaSAR descriptors of molecular operating environment (MOE) employing computer-assisted multiple regression procedure. The generated QSAR models revealed that factors related to hydrophobicity, molecular shape and geometry predominantly influences glucagon receptor binding affinity of the triaryl imidazoles indicating the relevance of shape specific steric interactions between the molecule and the receptor. Further, QSAR models formulated for selective inhibition of glucagon receptor over p38 mitogen activated protein (MAP) kinase of the compounds in the series highlights that the same structural features, which influence the glucagon receptor affinity, also contribute to their selective inhibition.
The Relationship between Retention and College Counseling for High-risk Students

ERIC Educational Resources Information Center

Bishop, Kyle K.

2016-01-01

The author used an archival study to explore the relationship between college counseling and retention. The cohort for this study was a college's 2006 class of full-time, 1st-year students (N = 429). The results of chi-square analyses and regression analyses indicated (a) a significant difference in retention between high-risk and low-risk…
Demystifying Multitask Deep Neural Networks for Quantitative Structure-Activity Relationships.

PubMed

Xu, Yuting; Ma, Junshui; Liaw, Andy; Sheridan, Robert P; Svetnik, Vladimir

2017-10-23

Deep neural networks (DNNs) are complex computational models that have found great success in many artificial intelligence applications, such as computer vision1,2 and natural language processing.3,4 In the past four years, DNNs have also generated promising results for quantitative structure-activity relationship (QSAR) tasks.5,6 Previous work showed that DNNs can routinely make better predictions than traditional methods, such as random forests, on a diverse collection of QSAR data sets. It was also found that multitask DNN models-those trained on and predicting multiple QSAR properties simultaneously-outperform DNNs trained separately on the individual data sets in many, but not all, tasks. To date there has been no satisfactory explanation of why the QSAR of one task embedded in a multitask DNN can borrow information from other unrelated QSAR tasks. Thus, using multitask DNNs in a way that consistently provides a predictive advantage becomes a challenge. In this work, we explored why multitask DNNs make a difference in predictive performance. Our results show that during prediction a multitask DNN does borrow "signal" from molecules with similar structures in the training sets of the other tasks. However, whether this borrowing leads to better or worse predictive performance depends on whether the activities are correlated. On the basis of this, we have developed a strategy to use multitask DNNs that incorporate prior domain knowledge to select training sets with correlated activities, and we demonstrate its effectiveness on several examples.
Evolution of the international workshops on quantitative structure-activity relationships (QSARs) in environmental toxicology.

PubMed

Kaiser, K L E

2007-01-01

This presentation will review the evolution of the workshops from a scientific and personal perspective. From their modest beginning in 1983, the workshops have developed into larger international meetings, regularly held every two years. Their initial focus on the aquatic sphere soon expanded to include properties and effects on atmospheric and terrestrial species, including man. Concurrent with this broadening of their scientific scope, the workshops have become an important forum for the early dissemination of all aspects of qualitative and quantitative structure-activity research in ecotoxicology and human health effects. Over the last few decades, the field of quantitative structure/activity relationships (QSARs) has quickly emerged as a major scientific method in understanding the properties and effects of chemicals on the environment and human health. From substances that only affect cell membranes to those that bind strongly to a specific enzyme, QSARs provides insight into the biological effects and chemical and physical properties of substances. QSARs are useful for delineating the quantitative changes in biological effects resulting from minor but systematic variations of the structure of a compound with a specific mode of action. In addition, more holistic approaches are being devised that result in our ability to predict the effects of structurally unrelated compounds with (potentially) different modes of action. Research in QSAR environmental toxicology has led to many improvements in the manufacturing, use, and disposal of chemicals. Furthermore, it has led to national policies and international agreements, from use restrictions or outright bans of compounds, such as polychlorinated biphenyls (PCBs), mirex, and highly chlorinated pesticides (e.g. DDT, dieldrin) for the protection of avian predators, to alternatives for ozone-depleting compounds, to better waste treatment systems, to more powerful and specific acting drugs. Most of the recent advances
Molecular Modeling on Berberine Derivatives toward BuChE: An Integrated Study with Quantitative Structure-Activity Relationships Models, Molecular Docking, and Molecular Dynamics Simulations.

PubMed

Fang, Jiansong; Pang, Xiaocong; Wu, Ping; Yan, Rong; Gao, Li; Li, Chao; Lian, Wenwen; Wang, Qi; Liu, Ai-lin; Du, Guan-hua

2016-05-01

A dataset of 67 berberine derivatives for the inhibition of butyrylcholinesterase (BuChE) was studied based on the combination of quantitative structure-activity relationships models, molecular docking, and molecular dynamics methods. First, a series of berberine derivatives were reported, and their inhibitory activities toward butyrylcholinesterase (BuChE) were evaluated. By 2D- quantitative structure-activity relationships studies, the best model built by partial least-square had a conventional correlation coefficient of the training set (R(2)) of 0.883, a cross-validation correlation coefficient (Qcv2) of 0.777, and a conventional correlation coefficient of the test set (Rpred2) of 0.775. The model was also confirmed by Y-randomization examination. In addition, the molecular docking and molecular dynamics simulation were performed to better elucidate the inhibitory mechanism of three typical berberine derivatives (berberine, C2, and C55) toward BuChE. The predicted binding free energy results were consistent with the experimental data and showed that the van der Waals energy term (ΔEvdw) difference played the most important role in differentiating the activity among the three inhibitors (berberine, C2, and C55). The developed quantitative structure-activity relationships models provide details on the fine relationship linking structure and activity and offer clues for structural modifications, and the molecular simulation helps to understand the inhibitory mechanism of the three typical inhibitors. In conclusion, the results of this study provide useful clues for new drug design and discovery of BuChE inhibitors from berberine derivatives. © 2015 John Wiley & Sons A/S.
Relationships Between Herpetofaunal Community Structure and Varying Levels of Overstory Tree Retention in Northern Alabama: First-year Results

Treesearch

Zachary I. Felix; Yong Wang; Callie Jo Schweitzer

2004-01-01

Forest managers are increasingly considering the effects their decisions have on the biodiversity of an area. However, there is often a lack of data upon which to evaluate these decisions. We conducted research to examine the relationship between silvicultural techniques, particularly shelterwood cuts with varying levels of basal area retention, and the community...

Quantitative structure-property relationships for prediction of boiling point, vapor pressure, and melting point.

PubMed

Dearden, John C

2003-08-01

Boiling point, vapor pressure, and melting point are important physicochemical properties in the modeling of the distribution and fate of chemicals in the environment. However, such data often are not available, and therefore must be estimated. Over the years, many attempts have been made to calculate boiling points, vapor pressures, and melting points by using quantitative structure-property relationships, and this review examines and discusses the work published in this area, and concentrates particularly on recent studies. A number of software programs are commercially available for the calculation of boiling point, vapor pressure, and melting point, and these have been tested for their predictive ability with a test set of 100 organic chemicals.
The Relationships Among Licensed Nurse Turnover, Retention, and Rehospitalization of Nursing Home Residents

PubMed Central

Thomas, Kali S.

2013-01-01

Purpose: Individuals receiving postacute care in skilled nursing facilities often require complex, skilled care provided by licensed nurses. It is believed that a stable set of nursing personnel is more likely to deliver better care. The purpose of this study was to determine the relationships among licensed nurse retention, turnover, and a 30-day rehospitalization rate in nursing homes (NHs). Design and Methods: We combined two data sources: NH facility-level data (including characteristics of the facility, the market, and residents) and the Florida Nursing Home Staffing Reports (which provide staffing information for each NH) for 681 Florida NHs from 2002 to 2009. Using a two-way fixed effects model, we examined the relationships among licensed nurse turnover rates, retention rates, and 30-day rehospitalization rates. Results: Results indicate that an NH’s licensed nurse retention rate is significantly associated with the 30-day rehospitalization rate (est. = −.02, p = .04) controlling for demographic characteristics of the patient population, residents’ preferences for hospitalization, and the ownership characteristics of the NH. The NHs experiencing a 10% increase in their licensed nurse retention had a 0.2% lower rehospitalization rate, which equates to 2 fewer hospitalizations per NH annually. Licensed nurse turnover is not significantly related to the 30-day rehospitalization rate. Implications: These findings highlight the need for NH administrators and policy makers to focus on licensed nurse retention, and future research should focus on the measures of staff retention for understanding the staffing/quality relationship. PMID:22936529
Quantitative structure-property relationship modeling of remote liposome loading of drugs.

PubMed

Cern, Ahuva; Golbraikh, Alexander; Sedykh, Aleck; Tropsha, Alexander; Barenholz, Yechezkel; Goldblum, Amiram

2012-06-10

Remote loading of liposomes by trans-membrane gradients is used to achieve therapeutically efficacious intra-liposome concentrations of drugs. We have developed Quantitative Structure Property Relationship (QSPR) models of remote liposome loading for a data set including 60 drugs studied in 366 loading experiments internally or elsewhere. Both experimental conditions and computed chemical descriptors were employed as independent variables to predict the initial drug/lipid ratio (D/L) required to achieve high loading efficiency. Both binary (to distinguish high vs. low initial D/L) and continuous (to predict real D/L values) models were generated using advanced machine learning approaches and 5-fold external validation. The external prediction accuracy for binary models was as high as 91-96%; for continuous models the mean coefficient R(2) for regression between predicted versus observed values was 0.76-0.79. We conclude that QSPR models can be used to identify candidate drugs expected to have high remote loading capacity while simultaneously optimizing the design of formulation experiments. Copyright © 2011 Elsevier B.V. All rights reserved.
HomoSAR: bridging comparative protein modeling with quantitative structural activity relationship to design new peptides.

PubMed

Borkar, Mahesh R; Pissurlenkar, Raghuvir R S; Coutinho, Evans C

2013-11-15

Peptides play significant roles in the biological world. To optimize activity for a specific therapeutic target, peptide library synthesis is inevitable; which is a time consuming and expensive. Computational approaches provide a promising way to simply elucidate the structural basis in the design of new peptides. Earlier, we proposed a novel methodology termed HomoSAR to gain insight into the structure activity relationships underlying peptides. Based on an integrated approach, HomoSAR uses the principles of homology modeling in conjunction with the quantitative structural activity relationship formalism to predict and design new peptide sequences with the optimum activity. In the present study, we establish that the HomoSAR methodology can be universally applied to all classes of peptides irrespective of sequence length by studying HomoSAR on three peptide datasets viz., angiotensin-converting enzyme inhibitory peptides, CAMEL-s antibiotic peptides, and hAmphiphysin-1 SH3 domain binding peptides, using a set of descriptors related to the hydrophobic, steric, and electronic properties of the 20 natural amino acids. Models generated for all three datasets have statistically significant correlation coefficients (r(2)) and predictive r2 (r(pred)2) and cross validated coefficient ( q(LOO)2). The daintiness of this technique lies in its simplicity and ability to extract all the information contained in the peptides to elucidate the underlying structure activity relationships. The difficulties of correlating both sequence diversity and variation in length of the peptides with their biological activity can be addressed. The study has been able to identify the preferred or detrimental nature of amino acids at specific positions in the peptide sequences. Copyright © 2013 Wiley Periodicals, Inc.
Nuclear reactor melt-retention structure to mitigate direct containment heating

DOEpatents

Tutu, Narinder K.; Ginsberg, Theodore; Klages, John R.

1991-01-01

A light water nuclear reactor melt-retention structure to mitigate the extent of direct containment heating of the reactor containment building. The structure includes a retention chamber for retaining molten core material away from the upper regions of the reactor containment building when a severe accident causes the bottom of the pressure vessel of the reactor to fail and discharge such molten material under high pressure through the reactor cavity into the retention chamber. In combination with the melt-retention chamber there is provided a passageway that includes molten core droplet deflector vanes and has gas vent means in its upper surface, which means are operable to deflect molten core droplets into the retention chamber while allowing high pressure steam and gases to be vented into the upper regions of the containment building. A plurality of platforms are mounted within the passageway and the melt-retention structure to direct the flow of molten core material and help retain it within the melt-retention chamber. In addition, ribs are mounted at spaced positions on the floor of the melt-retention chamber, and grid means are positioned at the entrance side of the retention chamber. The grid means develop gas back pressure that helps separate the molten core droplets from discharged high pressure steam and gases, thereby forcing the steam and gases to vent into the upper regions of the reactor containment building.
Design and prediction of new anticoagulants as a selective Factor IXa inhibitor via three-dimensional quantitative structure-property relationships of amidinobenzothiophene derivatives.

PubMed

Gao, Jia-Suo; Tong, Xu-Peng; Chang, Yi-Qun; He, Yu-Xuan; Mei, Yu-Dan; Tan, Pei-Hong; Guo, Jia-Liang; Liao, Guo-Chao; Xiao, Gao-Keng; Chen, Wei-Min; Zhou, Shu-Feng; Sun, Ping-Hua

2015-01-01

Factor IXa (FIXa), a blood coagulation factor, is specifically inhibited at the initiation stage of the coagulation cascade, promising an excellent approach for developing selective and safe anticoagulants. Eighty-four amidinobenzothiophene antithrombotic derivatives targeting FIXa were selected to establish three-dimensional quantitative structure-activity relationship (3D-QSAR) and three-dimensional quantitative structure-selectivity relationship (3D-QSSR) models using comparative molecular field analysis and comparative similarity indices analysis methods. Internal and external cross-validation techniques were investigated as well as region focusing and bootstrapping. The satisfactory q (2) values of 0.753 and 0.770, and r (2) values of 0.940 and 0.965 for 3D-QSAR and 3D-QSSR, respectively, indicated that the models are available to predict both the inhibitory activity and selectivity on FIXa against Factor Xa, the activated status of Factor X. This work revealed that the steric, hydrophobic, and H-bond factors should appropriately be taken into account in future rational design, especially the modifications at the 2'-position of the benzene and the 6-position of the benzothiophene in the R group, providing helpful clues to design more active and selective FIXa inhibitors for the treatment of thrombosis. On the basis of the three-dimensional quantitative structure-property relationships, 16 new potent molecules have been designed and are predicted to be more active and selective than Compound 33, which has the best activity as reported in the literature.
Online Mate-Retention Tactics on Facebook Are Associated With Relationship Aggression.

PubMed

Brem, Meagan J; Spiller, Laura C; Vandehey, Michael A

2015-10-01

A measure of Facebook-related mate-retention tactics was developed to investigate the relationship between online behaviors and intimate partner aggression. One hundred and seventy-seven young adults (65 men, 112 women) completed questionnaires that included measures of online and offline mate-retention tactics, Facebook jealousy, Facebook surveillance, and intimate partner violence. A factor analysis yielded four subscales for the Facebook Mate-Retention Tactic Inventory (FMRTI): Care and Affection, Jealousy and Surveillance, Possession Signals, and Punishment of Infidelity Threat. The FMRTI total scores were positively correlated with Facebook jealousy, Facebook surveillance, and use of offline mate-retention tactics. The Jealousy and Surveillance subscale uniquely predicted intimate partner psychological and physical aggression over and above existing measures. Facebook mate-retention tactics fully mediated the relation between Facebook jealousy and both intimate partner psychological and physical aggression. The current study provides preliminary evidence for conceptualizing Facebook as an environment for the use of mate-retention tactics that have real-life implications for intimate partner violence. © The Author(s) 2014.
Molecular design of anticancer drug leads based on three-dimensional quantitative structure-activity relationship.

PubMed

Huang, Xiao Yan; Shan, Zhi Jie; Zhai, Hong Lin; Li, Li Na; Zhang, Xiao Yun

2011-08-22

Heat shock protein 90 (Hsp90) takes part in the developments of several cancers. Novobiocin, a typically C-terminal inhibitor for Hsp90, will probably used as an important anticancer drug in the future. In this work, we explored the valuable information and designed new novobiocin derivatives based on a three-dimensional quantitative structure-activity relationship (3D QSAR). The comparative molecular field analysis and comparative molecular similarity indices analysis models with high predictive capability were established, and their reliabilities are supported by the statistical parameters. Based on the several important influence factors obtained from these models, six new novobiocin derivatives with higher inhibitory activities were designed and confirmed by the molecular simulation with our models, which provide the potential anticancer drug leads for further research.
Synthesis, quantitative structure-property relationship study of novel fluorescence active 2-pyrazolines and application.

PubMed

Girgis, Adel S; Basta, Altaf H; El-Saied, Houssni; Mohamed, Mohamed A; Bedair, Ahmad H; Salim, Ahmad S

2018-03-01

A variety of fluorescence-active fluorinated pyrazolines 13-33 was synthesized in good yields through cyclocondensation reaction of propenones 1-9 with aryl hydrazines 10-12 . Some of the synthesized compounds provided promising fluorescence properties with quantum yield ( Φ ) higher than that of quinine sulfate (standard reference). Quantitative structure-property relationship studies were undertaken supporting the exhibited fluorescence properties and estimating the parameters governing properties. Five synthesized fluorescence-active pyrazolines ( 13 , 15 , 18 , 19 and 23 ) with variable Φ were selected for treating two types of paper sheets (Fabriano and Bible paper). These investigated fluorescence compounds, especially compounds 19 and 23 , provide improvements in strength properties of paper sheets. Based on the observed performance they can be used as markers in security documents.
Synthesis, quantitative structure-property relationship study of novel fluorescence active 2-pyrazolines and application

NASA Astrophysics Data System (ADS)

Girgis, Adel S.; Basta, Altaf H.; El-Saied, Houssni; Mohamed, Mohamed A.; Bedair, Ahmad H.; Salim, Ahmad S.

2018-03-01

A variety of fluorescence-active fluorinated pyrazolines 13-33 was synthesized in good yields through cyclocondensation reaction of propenones 1-9 with aryl hydrazines 10-12. Some of the synthesized compounds provided promising fluorescence properties with quantum yield (Φ) higher than that of quinine sulfate (standard reference). Quantitative structure-property relationship studies were undertaken supporting the exhibited fluorescence properties and estimating the parameters governing properties. Five synthesized fluorescence-active pyrazolines (13, 15, 18, 19 and 23) with variable Φ were selected for treating two types of paper sheets (Fabriano and Bible paper). These investigated fluorescence compounds, especially compounds 19 and 23, provide improvements in strength properties of paper sheets. Based on the observed performance they can be used as markers in security documents.
Quantitative Structure Retention Relationships of Polychlorinated Dibenzodioxins and Dibenzofurans

DTIC Science & Technology

1991-08-01

be a projection onto the X-Y plane. The algorithm for this calculation can be found in Stouch and Jurs (22), but was further refined by Rohrbaugh and...throughspace distances. WPSA2 (c) Weighted positive charged surface area. MOMH2 (c) Second major moment of inertia with hydrogens attached. CSTR 3 (d) Sum...of the models. The robust regression analysis method calculates a regression model using a least median squares algorithm which is not as susceptible
Obscure phenomena in statistical analysis of quantitative structure-activity relationships. Part 1: Multicollinearity of physicochemical descriptors.

PubMed

Mager, P P; Rothe, H

1990-10-01

Multicollinearity of physicochemical descriptors leads to serious consequences in quantitative structure-activity relationship (QSAR) analysis, such as incorrect estimators and test statistics of regression coefficients of the ordinary least-squares (OLS) model applied usually to QSARs. Beside the diagnosis of the known simple collinearity, principal component regression analysis (PCRA) also allows the diagnosis of various types of multicollinearity. Only if the absolute values of PCRA estimators are order statistics that decrease monotonically, the effects of multicollinearity can be circumvented. Otherwise, obscure phenomena may be observed, such as good data recognition but low predictive model power of a QSAR model.
A thorough experimental study of CH/π interactions in water: quantitative structure-stability relationships for carbohydrate/aromatic complexes.

PubMed

Jiménez-Moreno, Ester; Jiménez-Osés, Gonzalo; Gómez, Ana M; Santana, Andrés G; Corzana, Francisco; Bastida, Agatha; Jiménez-Barbero, Jesus; Asensio, Juan Luis

2015-11-13

CH/π interactions play a key role in a large variety of molecular recognition processes of biological relevance. However, their origins and structural determinants in water remain poorly understood. In order to improve our comprehension of these important interaction modes, we have performed a quantitative experimental analysis of a large data set comprising 117 chemically diverse carbohydrate/aromatic stacking complexes, prepared through a dynamic combinatorial approach recently developed by our group. The obtained free energies provide a detailed picture of the structure-stability relationships that govern the association process, opening the door to the rational design of improved carbohydrate-based ligands or carbohydrate receptors. Moreover, this experimental data set, supported by quantum mechanical calculations, has contributed to the understanding of the main driving forces that promote complex formation, underlining the key role played by coulombic and solvophobic forces on the stabilization of these complexes. This represents the most quantitative and extensive experimental study reported so far for CH/π complexes in water.
Quantitative structure-activity relationships for green algae growth inhibition by polymer particles.

PubMed

Nolte, Tom M; Peijnenburg, Willie J G M; Hendriks, A Jan; van de Meent, Dik

2017-07-01

After use and disposal of chemical products, many types of polymer particles end up in the aquatic environment with potential toxic effects to primary producers like green algae. In this study, we have developed Quantitative Structure-Activity Relationships (QSARs) for a set of highly structural diverse polymers which are capable to estimate green algae growth inhibition (EC50). The model (N = 43, R 2 = 0.73, RMSE = 0.28) is a regression-based decision tree using one structural descriptor for each of three polymer classes separated based on charge. The QSAR is applicable to linear homo polymers as well as copolymers and does not require information on the size of the polymer particle or underlying core material. Highly branched polymers, non-nitrogen cationic polymers and polymeric surfactants are not included in the model and thus cannot be evaluated. The model works best for cationic and non-ionic polymers for which cellular adsorption, disruption of the cell wall and photosynthesis inhibition were the mechanisms of action. For anionic polymers, specific properties of the polymer and test characteristics need to be known for detailed assessment. The data and QSAR results for anionic polymers, when combined with molecular dynamics simulations indicated that nutrient depletion is likely the dominant mode of toxicity. Nutrient depletion in turn, is determined by the non-linear interplay between polymer charge density and backbone flexibility. Copyright © 2017 Elsevier Ltd. All rights reserved.
Non-linear quantitative structure-activity relationship for adenine derivatives as competitive inhibitors of adenosine deaminase

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

Sadat Hayatshahi, Sayyed Hamed; Abdolmaleki, Parviz; Safarian, Shahrokh

2005-12-16

Logistic regression and artificial neural networks have been developed as two non-linear models to establish quantitative structure-activity relationships between structural descriptors and biochemical activity of adenosine based competitive inhibitors, toward adenosine deaminase. The training set included 24 compounds with known k {sub i} values. The models were trained to solve two-class problems. Unlike the previous work in which multiple linear regression was used, the highest of positive charge on the molecules was recognized to be in close relation with their inhibition activity, while the electric charge on atom N1 of adenosine was found to be a poor descriptor. Consequently, themore » previously developed equation was improved and the newly formed one could predict the class of 91.66% of compounds correctly. Also optimized 2-3-1 and 3-4-1 neural networks could increase this rate to 95.83%.« less
Antitumor activity of 3,4-ethylenedioxythiophene derivatives and quantitative structure-activity relationship analysis

NASA Astrophysics Data System (ADS)

Jukić, Marijana; Rastija, Vesna; Opačak-Bernardi, Teuta; Stolić, Ivana; Krstulović, Luka; Bajić, Miroslav; Glavaš-Obrovac, Ljubica

2017-04-01

The aim of this study was to evaluate nine newly synthesized amidine derivatives of 3,4- ethylenedioxythiophene (3,4-EDOT) for their cytotoxic activity against a panel of human cancer cell lines and to perform a quantitative structure-activity relationship (QSAR) analysis for the antitumor activity of a total of 27 3,4-ethylenedioxythiophene derivatives. Induction of apoptosis was investigated on the selected compounds, along with delivery options for the optimization of activity. The best obtained QSAR models include the following group of descriptors: BCUT, WHIM, 2D autocorrelations, 3D-MoRSE, GETAWAY descriptors, 2D frequency fingerprint and information indices. Obtained QSAR models should be relieved in elucidation of important physicochemical and structural requirements for this biological activity. Highly potent molecules have a symmetrical arrangement of substituents along the x axis, high frequency of distance between N and O atoms at topological distance 9, as well as between C and N atoms at topological distance 10, and more C atoms located at topological distances 6 and 3. Based on the conclusion given in the QSAR analysis, a new compound with possible great activity was proposed.
Quantitative structure activity relationship (QSAR) of piperine analogs for bacterial NorA efflux pump inhibitors.

PubMed

Nargotra, Amit; Sharma, Sujata; Koul, Jawahir Lal; Sangwan, Pyare Lal; Khan, Inshad Ali; Kumar, Ashwani; Taneja, Subhash Chander; Koul, Surrinder

2009-10-01

Quantitative structure activity relationship (QSAR) analysis of piperine analogs as inhibitors of efflux pump NorA from Staphylococcus aureus has been performed in order to obtain a highly accurate model enabling prediction of inhibition of S. aureus NorA of new chemical entities from natural sources as well as synthetic ones. Algorithm based on genetic function approximation method of variable selection in Cerius2 was used to generate the model. Among several types of descriptors viz., topological, spatial, thermodynamic, information content and E-state indices that were considered in generating the QSAR model, three descriptors such as partial negative surface area of the compounds, area of the molecular shadow in the XZ plane and heat of formation of the molecules resulted in a statistically significant model with r(2)=0.962 and cross-validation parameter q(2)=0.917. The validation of the QSAR models was done by cross-validation, leave-25%-out and external test set prediction. The theoretical approach indicates that the increase in the exposed partial negative surface area increases the inhibitory activity of the compound against NorA whereas the area of the molecular shadow in the XZ plane is inversely proportional to the inhibitory activity. This model also explains the relationship of the heat of formation of the compound with the inhibitory activity. The model is not only able to predict the activity of new compounds but also explains the important regions in the molecules in quantitative manner.
Quantitative Structure – Property Relationship Modeling of Remote Liposome Loading Of Drugs

PubMed Central

Cern, Ahuva; Golbraikh, Alexander; Sedykh, Aleck; Tropsha, Alexander; Barenholz, Yechezkel; Goldblum, Amiram

2012-01-01

Remote loading of liposomes by trans-membrane gradients is used to achieve therapeutically efficacious intra-liposome concentrations of drugs. We have developed Quantitative Structure Property Relationship (QSPR) models of remote liposome loading for a dataset including 60 drugs studied in 366 loading experiments internally or elsewhere. Both experimental conditions and computed chemical descriptors were employed as independent variables to predict the initial drug/lipid ratio (D/L) required to achieve high loading efficiency. Both binary (to distinguish high vs. low initial D/L) and continuous (to predict real D/L values) models were generated using advanced machine learning approaches and five-fold external validation. The external prediction accuracy for binary models was as high as 91–96%; for continuous models the mean coefficient R2 for regression between predicted versus observed values was 0.76–0.79. We conclude that QSPR models can be used to identify candidate drugs expected to have high remote loading capacity while simultaneously optimizing the design of formulation experiments. PMID:22154932
Connecting students to institutions: the relationship between program resources and student retention in respiratory care education programs.

PubMed

Ari, Arzu

2009-09-01

Respiratory care education programs are being held accountable for student retention. Increasing student retention is necessary for the respiratory therapy profession, which suffers from a shortage of qualified therapists needed to meet the increased demand. The present study investigated the relationship between student retention rate and program resources, in order to understand which and to what extent the different components of program resources predict student retention rate. The target population of this study was baccalaureate of science degree respiratory care education programs. After utilizing a survey research method, Pearson correlations and multiple regression analysis were used for data analysis. With a 63% response rate (n = 36), this study found a statistically significant relationship between program resources and student retention rate. Financial and personnel resources had a statistically significant positive relationship with student retention. The mean financial resources per student was responsible for 33% of the variance in student retention, while the mean personnel resources per student accounted for 12% of the variance in student retention. Program financial resources available to students was the single best predictor of program performance on student retention. Respiratory care education programs spending more money per student and utilizing more personnel in the program have higher mean performance in student retention. Therefore, respiratory care education programs must devote sufficient resources to retaining students so that they can produce more respiratory therapists and thereby make the respiratory therapy profession stronger.
An Exploration of the Relationship between Religiosity and Retention

ERIC Educational Resources Information Center

Butterfield, Rex M.; Pemberton, Cynthia Lee A.

2011-01-01

The purpose of this study was to explore the relationship between religiosity and retention at Idaho State University (ISU). Attrition is a problem that has, and continues to plague higher education. Research shows that students who are more integrated in education (both in and out of class) are more likely to remain enrolled. For this study,…

On the virtues of automated quantitative structure-activity relationship: the new kid on the block.

PubMed

de Oliveira, Marcelo T; Katekawa, Edson

2018-02-01

Quantitative structure-activity relationship (QSAR) has proved to be an invaluable tool in medicinal chemistry. Data availability at unprecedented levels through various databases have collaborated to a resurgence in the interest for QSAR. In this context, rapid generation of quality predictive models is highly desirable for hit identification and lead optimization. We showcase the application of an automated QSAR approach, which randomly selects multiple training/test sets and utilizes machine-learning algorithms to generate predictive models. Results demonstrate that AutoQSAR produces models of improved or similar quality to those generated by practitioners in the field but in just a fraction of the time. Despite the potential of the concept to the benefit of the community, the AutoQSAR opportunity has been largely undervalued.
AutoQSAR: an automated machine learning tool for best-practice quantitative structure-activity relationship modeling.

PubMed

Dixon, Steven L; Duan, Jianxin; Smith, Ethan; Von Bargen, Christopher D; Sherman, Woody; Repasky, Matthew P

2016-10-01

We introduce AutoQSAR, an automated machine-learning application to build, validate and deploy quantitative structure-activity relationship (QSAR) models. The process of descriptor generation, feature selection and the creation of a large number of QSAR models has been automated into a single workflow within AutoQSAR. The models are built using a variety of machine-learning methods, and each model is scored using a novel approach. Effectiveness of the method is demonstrated through comparison with literature QSAR models using identical datasets for six end points: protein-ligand binding affinity, solubility, blood-brain barrier permeability, carcinogenicity, mutagenicity and bioaccumulation in fish. AutoQSAR demonstrates similar or better predictive performance as compared with published results for four of the six endpoints while requiring minimal human time and expertise.
Utilization of quantitative structure-activity relationships (QSARs) in risk assessment: Alkylphenols

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

Beck, B.D.; Toole, A.P.; Callahan, B.G.

1991-12-01

Alkylphenols are a class of environmentally pervasive compounds, found both in natural (e.g., crude oils) and in anthropogenic (e.g., wood tar, coal gasification waste) materials. Despite the frequent environmental occurrence of these chemicals, there is a limited toxicity database on alkylphenols. The authors have therefore developed a 'toxicity equivalence approach' for alkylphenols which is based on their ability to inhibit, in a specific manner, the enzyme cyclooxygenase. Enzyme-inhibiting ability for individual alkylphenols can be estimated based on the quantitative structure-activity relationship developed by Dewhirst (1980) and is a function of the free hydroxyl group, electron-donating ring substituents, and hydrophobic aromaticmore » ring substituents. The authors evaluated the toxicological significance of cyclooxygenase inhibition by comparison of the inhibitory capacity of alkylphenols with the inhibitory capacity of acetylsalicylic acid, or aspirin, a compound whose low-level effects are due to cyclooxygenase inhibition. Since nearly complete absorption for alkylphenols and aspirin is predicted, based on estimates of hydrophobicity and fraction of charged molecules at gastrointestinal pHs, risks from alkylphenols can be expressed directly in terms of 'milligram aspirin equivalence,' without correction for absorption differences. They recommend this method for assessing risks of mixtures of alkylphenols, especially for those compounds with no chronic toxicity data.38 references.« less
Whose Responsibility Is It? Advising and Retention among Undergraduates

ERIC Educational Resources Information Center

Coleman, Amanda Y.

2013-01-01

Student retention continues to be a major concern in higher education. Every year many individuals enroll in higher education institutions but never obtain a certificate or degree within a six-year span. The following quantitative descriptive-comparative study addressed how academic advisors' relationships with advisees may affect student…
Structural Information Retention in Visual Art Processing.

ERIC Educational Resources Information Center

Koroscik, Judith Smith

The accuracy of non-art college students' longterm retention of structural information presented in Leonardo da Vinci's "Mona Lisa" was tested. Seventeen female undergraduates viewed reproductions of the painting and copies that closely resembled structural attributes of the original. Only 3 of the 17 subjects reported having viewed a reproduction…
Predicting total organic halide formation from drinking water chlorination using quantitative structure-property relationships.

PubMed

Luilo, G B; Cabaniss, S E

2011-10-01

Chlorinating water which contains dissolved organic matter (DOM) produces disinfection byproducts, the majority of unknown structure. Hence, the total organic halide (TOX) measurement is used as a surrogate for toxic disinfection byproducts. This work derives a robust quantitative structure-property relationship (QSPR) for predicting the TOX formation potential of model compounds. Literature data for 49 compounds were used to train the QSPR in moles of chlorine per mole of compound (Cp) (mol-Cl/mol-Cp). The resulting QSPR has four descriptors, calibration [Formula: see text] of 0.72 and standard deviation of estimation of 0.43 mol-Cl/mol-Cp. Internal and external validation indicate that the QSPR has good predictive power and low bias (<1%). Applying this QSPR to predict TOX formation by DOM surrogates - tannic acid, two model fulvic acids and two agent-based model assemblages - gave a predicted TOX range of 136-184 µg-Cl/mg-C, consistent with experimental data for DOM, which ranged from 78 to 192 µg-Cl/mg-C. However, the limited structural variation in the training data may limit QSPR applicability; studies of more sulfur-containing compounds, heterocyclic compounds and high molecular weight compounds could lead to a more widely applicable QSPR.
Quantitative structure-permeability relationships at various pH values for acidic and basic drugs and drug-like compounds.

PubMed

Oja, M; Maran, U

2015-01-01

Absorption in gastrointestinal tract compartments varies and is largely influenced by pH. Therefore, considering pH in studies and analyses of membrane permeability provides an opportunity to gain a better understanding of the behaviour of compounds and to obtain good permeability estimates for prediction purposes. This study concentrates on relationships between the chemical structure and membrane permeability of acidic and basic drugs and drug-like compounds. The membrane permeability of 36 acidic and 61 basic compounds was measured using the parallel artificial membrane permeability assay (PAMPA) at pH 3, 5, 7.4 and 9. Descriptive and/or predictive single-parameter quantitative structure-permeability relationships were derived for all pH values. For acidic compounds, membrane permeability is mainly influenced by hydrogen bond donor properties, as revealed by models with r(2) > 0.8 for pH 3 and pH 5. For basic compounds, the best (r(2) > 0.7) structure-permeability relationships are obtained with the octanol-water distribution coefficient for pH 7.4 and pH 9, indicating the importance of partition properties. In addition to the validation set, the prediction quality of the developed models was tested with folic acid and astemizole, showing good matches between experimental and calculated membrane permeabilities at key pHs. Selected QSAR models are available at the QsarDB repository ( http://dx.doi.org/10.15152/QDB.166 ).
On the Development and Use of Large Chemical Similarity Networks, Informatics Best Practices and Novel Chemical Descriptors towards Materials Quantitative Structure Property Relationships

ERIC Educational Resources Information Center

Krein, Michael

2011-01-01

After decades of development and use in a variety of application areas, Quantitative Structure Property Relationships (QSPRs) and related descriptor-based statistical learning methods have achieved a level of infamy due to their misuse. The field is rife with past examples of overtrained models, overoptimistic performance assessment, and outright…
THE PRACTICE OF STRUCTURE ACTIVITY RELATIONSHIPS (SAR) IN TOXICOLOGY

EPA Science Inventory

Both qualitative and quantitative modeling methods relating chemical structure to biological activity, called structure-activity relationship analyses or SAR, are applied to the prediction and characterization of chemical toxicity. This minireview will discuss some generic issue...
PLS-based quantitative structure-activity relationship for substituted benzamides of clebopride type. Application of experimental design in drug design.

PubMed

Norinder, U; Högberg, T

1992-04-01

The advantageous approach of using an experimentally designed training set as the basis for establishing a quantitative structure-activity relationship with good predictive capability is described. The training set was selected from a fractional factorial design scheme based on a principal component description of physico-chemical parameters of aromatic substituents. The derived model successfully predicts the activities of additional substituted benzamides of 6-methoxy-N-(4-piperidyl)salicylamide type. The major influence on activity of the 3-substituent is demonstrated.
Design of cinnamaldehyde amino acid Schiff base compounds based on the quantitative structure-activity relationship.

PubMed

Wang, Hui; Jiang, Mingyue; Li, Shujun; Hse, Chung-Yun; Jin, Chunde; Sun, Fangli; Li, Zhuo

2017-09-01

Cinnamaldehyde amino acid Schiff base (CAAS) is a new class of safe, bioactive compounds which could be developed as potential antifungal agents for fungal infections. To design new cinnamaldehyde amino acid Schiff base compounds with high bioactivity, the quantitative structure-activity relationships (QSARs) for CAAS compounds against Aspergillus niger ( A. niger ) and Penicillium citrinum (P. citrinum) were analysed. The QSAR models ( R 2 = 0.9346 for A. niger , R 2 = 0.9590 for P. citrinum, ) were constructed and validated. The models indicated that the molecular polarity and the Max atomic orbital electronic population had a significant effect on antifungal activity. Based on the best QSAR models, two new compounds were designed and synthesized. Antifungal activity tests proved that both of them have great bioactivity against the selected fungi.
Deep neural nets as a method for quantitative structure-activity relationships.

PubMed

Ma, Junshui; Sheridan, Robert P; Liaw, Andy; Dahl, George E; Svetnik, Vladimir

2015-02-23

Neural networks were widely used for quantitative structure-activity relationships (QSAR) in the 1990s. Because of various practical issues (e.g., slow on large problems, difficult to train, prone to overfitting, etc.), they were superseded by more robust methods like support vector machine (SVM) and random forest (RF), which arose in the early 2000s. The last 10 years has witnessed a revival of neural networks in the machine learning community thanks to new methods for preventing overfitting, more efficient training algorithms, and advancements in computer hardware. In particular, deep neural nets (DNNs), i.e. neural nets with more than one hidden layer, have found great successes in many applications, such as computer vision and natural language processing. Here we show that DNNs can routinely make better prospective predictions than RF on a set of large diverse QSAR data sets that are taken from Merck's drug discovery effort. The number of adjustable parameters needed for DNNs is fairly large, but our results show that it is not necessary to optimize them for individual data sets, and a single set of recommended parameters can achieve better performance than RF for most of the data sets we studied. The usefulness of the parameters is demonstrated on additional data sets not used in the calibration. Although training DNNs is still computationally intensive, using graphical processing units (GPUs) can make this issue manageable.
Mate retention behavior of men and women in heterosexual and homosexual relationships.

PubMed

Vanderlaan, Doug P; Vasey, Paul L

2008-08-01

Comparing the behavior of heterosexual and homosexual persons can provide insight into the origins of heterosexual sex differences in psychology. Evidence indicates that, aside from sexual partner preference, the mating psychology of homosexual men is sex-typical whereas that of homosexual women tends to be more sex-atypical. The current study examined one aspect of mating psychology, mate retention behavior, and tested whether homosexual men and women were sex-typical or sex-atypical for those mate retention tactics where heterosexual men and women differed. Men and women in heterosexual and homosexual relationships were asked to provide information regarding their partners' mate retention behavior by using the Mate Retention Inventory Questionnaire. Heterosexual men and women differed significantly for six of the 19 mate retention tactics considered. With respect to the six mate retention tactics where heterosexual sex differences existed, homosexual men behaved in a sex-typical manner for five of the tactics, whereas homosexual women behaved in a sex-atypical manner for all six tactics. We discuss the significance of these findings for explaining the origins of the mate retention behavior of heterosexual men and women. In addition, we consider what the pattern of sex-typical and sex-atypical mating psychology among homosexual men and women, respectively, suggests in regard to sex differences in the development of mating psychology and the development of homosexual persons.
Development of quantitative structure-activity relationships and its application in rational drug design.

PubMed

Yang, Guang-Fu; Huang, Xiaoqin

2006-01-01

Over forty years have elapsed since Hansch and Fujita published their pioneering work of quantitative structure-activity relationships (QSAR). Following the introduction of Comparative Molecular Field Analysis (CoMFA) by Cramer in 1998, other three-dimensional QSAR methods have been developed. Currently, combination of classical QSAR and other computational techniques at three-dimensional level is of greatest interest and generally used in the process of modern drug discovery and design. During the last several decades, a number of different mythologies incorporating a range of molecular descriptors and different statistical regression ways have been proposed and successfully applied in developing of new drugs, thus QSAR method has been proven to be indispensable in not only the reliable prediction of specific properties of new compounds, but also the help to elucidate the possible molecular mechanism of the receptor-ligand interactions. Here, we review the recent developments in QSAR and their applications in rational drug design, focusing on the reasonable selection of novel molecular descriptors and the construction of predictive QSAR models by the help of advanced computational techniques.
Quantitative structure-activity relationships by neural networks and inductive logic programming. II. The inhibition of dihydrofolate reductase by triazines

NASA Astrophysics Data System (ADS)

Hirst, Jonathan D.; King, Ross D.; Sternberg, Michael J. E.

1994-08-01

One of the largest available data sets for developing a quantitative structure-activity relationship (QSAR) — the inhibition of dihydrofolate reductase (DHFR) by 2,4-diamino-6,6-dimethyl-5-phenyl-dihydrotriazine derivatives — has been used for a sixfold cross-validation trial of neural networks, inductive logic programming (ILP) and linear regression. No statistically significant difference was found between the predictive capabilities of the methods. However, the representation of molecules by attributes, which is integral to the ILP approach, provides understandable rules about drug-receptor interactions.
Social, structural, behavioral and clinical factors influencing retention in Pre-Exposure Prophylaxis (PrEP) care in Mississippi.

PubMed

Arnold, Trisha; Brinkley-Rubinstein, Lauren; Chan, Philip A; Perez-Brumer, Amaya; Bologna, Estefany S; Beauchamps, Laura; Johnson, Kendra; Mena, Leandro; Nunn, Amy

2017-01-01

Pre-exposure prophylaxis (PrEP) is a biomedical intervention that can reduce rates of HIV transmission when taken once daily by HIV-negative individuals. Little is understood about PrEP uptake and retention in care among the populations most heavily impacted by the HIV epidemic, particularly among young men who have sex with men (YMSM) in the Deep South. Therefore, this study explored the structural, social, behavioral, and clinical factors that affect PrEP use and retention in care among YMSM in Jackson, Mississippi. Thirty MSM who were prescribed PrEP at an outpatient primary care clinic were interviewed and included 23 men who had been retained in PrEP care and seven who had not been retained. The mean age of participants was 26.6 years. Most (23) participants were African American. Major factors affecting PrEP use and retention in PrEP care included 1) structural factors such as cost and access to financial assistance for medications and clinical services; 2) social factors such as stigma and relationship status; 3) behavioral factors including sexual risk behaviors; and 4) clinical factors such as perceived and actual side effects. Many participants also discussed the positive spillover effects of PrEP use and reported that PrEP had a positive impact on their health. Four of the seven individuals who had not been retained re-enrolled in PrEP care after completing their interviews, suggesting that case management and ongoing outreach can enhance retention in PrEP care. Interventions to enhance retention in PrEP care among MSM in the Deep South will be most effective if they address the complex structural, social, clinical, and behavioral factors that influence PrEP uptake and retention in PrEP care.
HPLC retention thermodynamics of grape and wine tannins.

PubMed

Barak, Jennifer A; Kennedy, James A

2013-05-08

The effect of grape and wine tannin structure on retention thermodynamics under reversed-phase high-performance liquid chromatography conditions on a polystyrene divinylbenzene column was investigated. On the basis of retention response to temperature, an alternative retention factor was developed to approximate the combined temperature response of the complex, unresolvable tannin mixture. This alternative retention factor was based upon relative tannin peak areas separated by an abrupt change in solvent gradient. Using this alternative retention factor, retention thermodynamics were calculated. Van't Hoff relationships of the natural log of the alternative retention factor against temperature followed Kirchoff's relationship. An inverse quadratic equation was fit to the data, and from this the thermodynamic parameters for tannin retention were calculated. All tannin fractions exhibited exothermic, spontaneous interaction, with enthalpy-entropy compensation observed. Normalizing for tannin size, distinct tannin compositional effects on thermodynamic parameters were observed. The results of this study indicate that HPLC can be valuable for measuring the thermodynamics of tannin interaction with a hydrophobic surface and provides a potentially valuable alternative to calorimetry. Furthermore, the information gathered may provide insight into understanding red wine astringency quality.
Three-dimensional quantitative structure-activity relationship studies on c-Src inhibitors based on different docking methods.

PubMed

Bairy, Santhosh Kumar; Suneel Kumar, B V S; Bhalla, Joseph Uday Tej; Pramod, A B; Ravikumar, Muttineni

2009-04-01

c-Src kinase play an important role in cell growth and differentiation and its inhibitors can be useful for the treatment of various diseases, including cancer, osteoporosis, and metastatic bone disease. Three dimensional quantitative structure-activity relationship (3D-QSAR) studies were carried out on quinazolin derivatives inhibiting c-Src kinase. Molecular field analysis (MFA) models with four different alignment techniques, namely, GLIDE, GOLD, LIGANDFIT and Least squares based methods were developed. glide based MFA model showed better results (Leave one out cross validation correlation coefficient r(2)(cv) = 0.923 and non-cross validation correlation coefficient r(2)= 0.958) when compared with other models. These results help us to understand the nature of descriptors required for activity of these compounds and thereby provide guidelines to design novel and potent c-Src kinase inhibitors.
Quantitative Relationships Involving Additive Differences: Numerical Resilience

ERIC Educational Resources Information Center

Ramful, Ajay; Ho, Siew Yin

2014-01-01

This case study describes the ways in which problems involving additive differences with unknown starting quantities, constrain the problem solver in articulating the inherent quantitative relationship. It gives empirical evidence to show how numerical reasoning takes over as a Grade 6 student instantiates the quantitative relation by resorting to…
MathPatch - Raising Retention and Performance in an Intro-geoscience Class by Raising Students' Quantitative Skills

NASA Astrophysics Data System (ADS)

Baer, E. M.; Whittington, C.; Burn, H.

2008-12-01

The geological sciences are fundamentally quantitative. However, the diversity of students' mathematical preparation and skills makes the successful use of quantitative concepts difficult in introductory level classes. At Highline Community College, we have implemented a one-credit co-requisite course to give students supplemental instruction for quantitative skills used in the course. The course, formally titled "Quantitative Geology," nicknamed "MathPatch," runs parallel to our introductory Physical Geology course. MathPatch teaches the quantitative skills required for the geology class right before they are needed. Thus, students learn only the skills they need and are given opportunities to apply them immediately. Topics include complex-graph reading, unit conversions, large numbers, scientific notation, scale and measurement, estimation, powers of 10, and other fundamental mathematical concepts used in basic geological concepts. Use of this course over the past 8 years has successfully accomplished the goals of increasing students' quantitative skills, success and retention. Students master the quantitative skills to a greater extent than before the course was implemented, and less time is spent covering basic quantitative skills in the classroom. Because the course supports the use of quantitative skills, the large number of faculty that teach Geology 101 are more comfortable in using quantitative analysis, and indeed see it as an expectation of the course at Highline. Also significant, retention in the geology course has increased substantially, from 75% to 85%. Although successful, challenges persist with requiring MathPatch as a supplementary course. One, we have seen enrollments decrease in Geology 101, which may be the result of adding this co-requisite. Students resist mandatory enrollment in the course, although they are not good at evaluating their own need for the course. The logistics utilizing MathPatch in an evening class with fewer and longer

2D- and 3D-quantitative structure-activity relationship studies for a series of phenazine N,N'-dioxide as antitumour agents.

PubMed

Cunha, Jonathan Da; Lavaggi, María Laura; Abasolo, María Inés; Cerecetto, Hugo; González, Mercedes

2011-12-01

Hypoxic regions of tumours are associated with increased resistance to radiation and chemotherapy. Nevertheless, hypoxia has been used as a tool for specific activation of some antitumour prodrugs, named bioreductive agents. Phenazine dioxides are an example of such bioreductive prodrugs. Our 2D-quantitative structure activity relationship studies established that phenazine dioxides electronic and lipophilic descriptors are related to survival fraction in oxia or in hypoxia. Additionally, statistically significant models, derived by partial least squares, were obtained between survival fraction in oxia and comparative molecular field analysis standard model (r² = 0.755, q² = 0.505 and F = 26.70) or comparative molecular similarity indices analysis-combined steric and electrostatic fields (r² = 0.757, q² = 0.527 and F = 14.93), and survival fraction in hypoxia and comparative molecular field analysis standard model (r² = 0.736, q² = 0.521 and F = 18.63) or comparative molecular similarity indices analysis-hydrogen bond acceptor field (r² = 0.858, q² = 0.737 and F = 27.19). Categorical classification was used for the biological parameter selective cytotoxicity emerging also good models, derived by soft independent modelling of class analogy, with both comparative molecular field analysis standard model (96% of overall classification accuracy) and comparative molecular similarity indices analysis-steric field (92% of overall classification accuracy). 2D- and 3D-quantitative structure-activity relationships models provided important insights into the chemical and structural basis involved in the molecular recognition process of these phenazines as bioreductive agents and should be useful for the design of new structurally related analogues with improved potency. © 2011 John Wiley & Sons A/S.
Quantifying the relationship between sequence and three-dimensional structure conservation in RNA

PubMed Central

2010-01-01

Background In recent years, the number of available RNA structures has rapidly grown reflecting the increased interest on RNA biology. Similarly to the studies carried out two decades ago for proteins, which gave the fundamental grounds for developing comparative protein structure prediction methods, we are now able to quantify the relationship between sequence and structure conservation in RNA. Results Here we introduce an all-against-all sequence- and three-dimensional (3D) structure-based comparison of a representative set of RNA structures, which have allowed us to quantitatively confirm that: (i) there is a measurable relationship between sequence and structure conservation that weakens for alignments resulting in below 60% sequence identity, (ii) evolution tends to conserve more RNA structure than sequence, and (iii) there is a twilight zone for RNA homology detection. Discussion The computational analysis here presented quantitatively describes the relationship between sequence and structure for RNA molecules and defines a twilight zone region for detecting RNA homology. Our work could represent the theoretical basis and limitations for future developments in comparative RNA 3D structure prediction. PMID:20550657
Predicting Factors of Perceived Organizational Support by Full-Time and Part-Time Community College Faculty as Relates to Student Retention Rates

ERIC Educational Resources Information Center

Nichols, Sarah K.

2012-01-01

Student retention is socially, politically, and financially important to educational institutions. This quantitative study explored the gap in research regarding the relationship between employment of part-time in lieu of full-time faculty and student retention. The campus climate exchange model (CCEM), served as the conceptual framework in this…
Quantitative Understanding of SHAPE Mechanism from RNA Structure and Dynamics Analysis.

PubMed

Hurst, Travis; Xu, Xiaojun; Zhao, Peinan; Chen, Shi-Jie

2018-05-10

The selective 2'-hydroxyl acylation analyzed by primer extension (SHAPE) method probes RNA local structural and dynamic information at single nucleotide resolution. To gain quantitative insights into the relationship between nucleotide flexibility, RNA 3D structure, and SHAPE reactivity, we develop a 3D Structure-SHAPE Relationship model (3DSSR) to rebuild SHAPE profiles from 3D structures. The model starts from RNA structures and combines nucleotide interaction strength and conformational propensity, ligand (SHAPE reagent) accessibility, and base-pairing pattern through a composite function to quantify the correlation between SHAPE reactivity and nucleotide conformational stability. The 3DSSR model shows the relationship between SHAPE reactivity and RNA structure and energetics. Comparisons between the 3DSSR-predicted SHAPE profile and the experimental SHAPE data show correlation, suggesting that the extracted analytical function may have captured the key factors that determine the SHAPE reactivity profile. Furthermore, the theory offers an effective method to sieve RNA 3D models and exclude models that are incompatible with experimental SHAPE data.
The confidence-accuracy relationship for eyewitness identification decisions: Effects of exposure duration, retention interval, and divided attention.

PubMed

Palmer, Matthew A; Brewer, Neil; Weber, Nathan; Nagesh, Ambika

2013-03-01

Prior research points to a meaningful confidence-accuracy (CA) relationship for positive identification decisions. However, there are theoretical grounds for expecting that different aspects of the CA relationship (calibration, resolution, and over/underconfidence) might be undermined in some circumstances. This research investigated whether the CA relationship for eyewitness identification decisions is affected by three, forensically relevant variables: exposure duration, retention interval, and divided attention at encoding. In Study 1 (N = 986), a field experiment, we examined the effects of exposure duration (5 s vs. 90 s) and retention interval (immediate testing vs. a 1-week delay) on the CA relationship. In Study 2 (N = 502), we examined the effects of attention during encoding on the CA relationship by reanalyzing data from a laboratory experiment in which participants viewed a stimulus video under full or divided attention conditions and then attempted to identify two targets from separate lineups. Across both studies, all three manipulations affected identification accuracy. The central analyses concerned the CA relation for positive identification decisions. For the manipulations of exposure duration and retention interval, overconfidence was greater in the more difficult conditions (shorter exposure; delayed testing) than the easier conditions. Only the exposure duration manipulation influenced resolution (which was better for 5 s than 90 s), and only the retention interval manipulation affected calibration (which was better for immediate testing than delayed testing). In all experimental conditions, accuracy and diagnosticity increased with confidence, particularly at the upper end of the confidence scale. Implications for theory and forensic settings are discussed.
Understanding ligninase-mediated reactions of endocrine disrupting chemicals in water: reaction rates and quantitative structure-activity relationships.

PubMed

Mao, Liang; Colosi, Lisa M; Gao, Shixiang; Huang, Qingguo

2011-07-15

We have verified in our previous work that lignin peroxidase (LiP) mediates effective removal of selected natural and synthetic estrogens. The efficiency of these reactions was greatly enhanced in the presence of veratryl alcohol (VA), a chemical that is produced along with LiP by certain white rot fungi, for example, Phanerochaete chrysosporium. In this study, we systematically evaluated the kinetic behaviors of LiP-mediated reactions for six endocrine disrupting compounds (EDCs), that is, steroid estrogens and their structural analogs, in both the presence and absence of VA. Resulting kinetic parameters were then correlated with structural features of LiP/substrate binding complexes, as quantified using molecular simulation, to create quantitative structure-activity relationship (QSAR) equations. These equations suggest that binding distance between a substrate's phenolic proton and δN of HIS47's imidazole ring plays an important role in modulating substrate reactivity toward LiP in both the presence and absence of VA. This information provides insight into an important enzymatic reaction process that occurs in the natural environment affecting EDC transformation, a process that may be used in engineered systems to achieve EDC removal from water.
Retention behaviour of polyunsaturated fatty acid methyl esters on porous graphitic carbon.

PubMed

Gaudin, Karen; Hanai, Toshihiko; Chaminade, Pierre; Baillet, Arlette

2007-07-20

Retention with porous graphitic carbon was investigated with 25 structures of fatty acid methyl esters (FAMEs) with two different mobile phases: CH(3)CN:CHCl(3) 60:40 (v/v) and CH(3)OH:CHCl(3) 60:40 (v/v) with both 0.1% triethylamine (TEA) and an equimolar amount of HCOOH. Preliminary results showed that the use of TEA/HCOOH led to the response increase of saturated FAMEs with evaporative light scattering detection. No increase was observed for unsaturated one. These modifiers may slightly reduce the retention of FAMEs but did not significantly modify the separation factor with porous graphitic carbon. Thermodynamic parameters were calculated for each structure using Van't Hoff plot measured over the temperature range from 10 to 50 degrees C, with the both mobile phase conditions. All the studied compounds were found linked by the same retention mechanism on porous graphitic carbon. Quantitative in silico analysis of the retention using a molecular mechanics calculation demonstrated a good correlation between the retention factors and the molecular interaction energy values (r>0.93). Especially the Van der Waals energy was predominant, and the contribution of electrostatic energy was negligible for the quantitative analysis of the retention. The results indicate that Van der Waals force, hydrophobic interaction, is predominant for the retention of FAMEs on this packing material. The relative retention for highly unsaturated homologues can be changed by the selection of the weak solvent CH(3)CN or CH(3)OH. Then isomers differing only in the position of the carbon double bond on the alkyl chain can be separated and their behaviour is summarised as the closer the carbon double bonds to the FAME polar head, the more the retention decreases. Finally, the more important the number of carbon double bonds in the alkyl chain is, the smaller the retention is.
Quantitative structure-property relationships for octanol-water partition coefficients of polybrominated diphenyl ethers.

PubMed

Li, Linnan; Xie, Shaodong; Cai, Hao; Bai, Xuetao; Xue, Zhao

2008-08-01

Theoretical molecular descriptors were tested against logK(OW) values for polybrominated diphenyl ethers (PBDEs) using the Partial Least-Squares Regression method which can be used to analyze data with many variables and few observations. A quantitative structure-property relationship (QSPR) model was successfully developed with a high cross-validated value (Q(cum)(2)) of 0.961, indicating a good predictive ability and stability of the model. The predictive power of the QSPR model was further cross-validated. The values of logK(OW) for PBDEs are mainly governed by molecular surface area, energy of the lowest unoccupied molecular orbital and the net atomic charges on the oxygen atom. All these descriptors have been discussed to interpret the partitioning mechanism of PBDE chemicals. The bulk property of the molecules represented by molecular surface area is the leading factor, and K(OW) values increase with the increase of molecular surface area. Higher energy of the lowest unoccupied molecular orbital and higher net atomic charge on the oxygen atom of PBDEs result in smaller K(OW). The energy of the lowest unoccupied molecular orbital and the net atomic charge on PBDEs oxygen also play important roles in affecting the partition of PBDEs between octanol and water by influencing the interactions between PBDEs and solvent molecules.
The quantitative structure-insecticidal activity relationships from plant derived compounds against chikungunya and zika Aedes aegypti (Diptera:Culicidae) vector.

PubMed

Saavedra, Laura M; Romanelli, Gustavo P; Rozo, Ciro E; Duchowicz, Pablo R

2018-01-01

The insecticidal activity of a series of 62 plant derived molecules against the chikungunya, dengue and zika vector, the Aedes aegypti (Diptera:Culicidae) mosquito, is subjected to a Quantitative Structure-Activity Relationships (QSAR) analysis. The Replacement Method (RM) variable subset selection technique based on Multivariable Linear Regression (MLR) proves to be successful for exploring 4885 molecular descriptors calculated with Dragon 6. The predictive capability of the obtained models is confirmed through an external test set of compounds, Leave-One-Out (LOO) cross-validation and Y-Randomization. The present study constitutes a first necessary computational step for designing less toxic insecticides. Copyright © 2017 Elsevier B.V. All rights reserved.
Relationship Building as a Retention Strategy: Linking Relationship Attitudes and Satisfaction Evaluations to Behavioral Outcomes.

ERIC Educational Resources Information Center

Bruning, Stephen D.

2002-01-01

Determines whether student-university relationship attitudes and satisfaction evaluations distinguished those who returned to a university from those who did not. Shows that respondent relationship attitudes differentiate those who returned to the university from those who did not, which provides a quantitative illustration of the benefits of…
[Topological models of retention index of thin-layer chromatogram for chiral organic acids].

PubMed

Li, Mingjian; Wang, Yuxiao; Feng, Hui; Feng, Changjun

2014-03-01

On the basis of Kier's molecular connectivity indices and conjugated matrix, novel molecular connectivity indices ((m) G(t)(v)) were defined and calculated for 18 chiral hydroxyl acids and amino acids. The chiral connectivity indices ((m)C(t)(v)) were introduced by extending (m)G(t)(v): (m)C(t)(v) = (m)G(t)(v) x w(j), where w(j) is the chiral index. The quantitative structure-retention index relationship (QSRR) between the retention index (R(M)) of thin-layer chromatogram for the chiral organic acids and (m)C(t)(v) was studied by multivariate statistical regression. By leaps-and-bounds regression analysis, the best four-parameter QSRR model was set up, and the traditional correlation coefficient (R2) and the cross-validation correlation coefficient (Q2) of leave-one-out (LOO) were 0.973 and 0.950, respectively. The results demonstrated that the model was highly reliable and had good predictive ability from the point of view of statistics. From the four parameters (0C(p)(v), 2C(p)(v), C(ch),(v), 5C(p)(v)) of the model, it is known that the dominant influence factors of the retention index were the molecular structure characteristics of two-dimensional and the space factors: the chiral characteristics, the flexibility and the puckered degree of molecules for the chiral organic acids. The results showed that the new parameter mC(t)(v) had good rationality and efficiency for the retention indices of the chiral organic acids. Therefore, an effective method was provided to predict the retention indices of the chiral organic acids.
Further evaluation of quantitative structure--activity relationship models for the prediction of the skin sensitization potency of selected fragrance allergens.

PubMed

Patlewicz, Grace Y; Basketter, David A; Pease, Camilla K Smith; Wilson, Karen; Wright, Zoe M; Roberts, David W; Bernard, Guillaume; Arnau, Elena Giménez; Lepoittevin, Jean-Pierre

2004-02-01

Fragrance substances represent a very diverse group of chemicals; a proportion of them are associated with the ability to cause allergic reactions in the skin. Efforts to find substitute materials are hindered by the need to undertake animal testing for determining both skin sensitization hazard and potency. One strategy to avoid such testing is through an understanding of the relationships between chemical structure and skin sensitization, so-called structure-activity relationships. In recent work, we evaluated 2 groups of fragrance chemicals -- saturated aldehydes and alpha,beta-unsaturated aldehydes. Simple quantitative structure-activity relationship (QSAR) models relating the EC3 values [derived from the local lymph node assay (LLNA)] to physicochemical properties were developed for both sets of aldehydes. In the current study, we evaluated an additional group of carbonyl-containing compounds to test the predictive power of the developed QSARs and to extend their scope. The QSAR models were used to predict EC3 values of 10 newly selected compounds. Local lymph node assay data generated for these compounds demonstrated that the original QSARs were fairly accurate, but still required improvement. Development of these QSAR models has provided us with a better understanding of the potential mechanisms of action for aldehydes, and hence how to avoid or limit allergy. Knowledge generated from this work is being incorporated into new/improved rules for sensitization in the expert toxicity prediction system, deductive estimation of risk from existing knowledge (DEREK).
Dehalogenation of persistent halogenated organic compounds: A review of computational studies and quantitative structure-property relationships.

PubMed

Luo, Jin; Hu, Jiwei; Wei, Xionghui; Fu, Liya; Li, Lingyun

2015-07-01

Dehalogenation is one of the highly important degradation reactions for halogenated organic compounds (HOCs) in the environment, which is also being developed as a potential type of the remediation technologies. In combination with the experimental results, intensive efforts have recently been devoted to the development of efficient theoretical methodologies (e.g. multi-scale simulation) to investigate the mechanisms for dehalogenation of HOCs. This review summarizes the structural characteristics of neutral molecules, anionic species and excited states of HOCs as well as their adsorption behavior on the surface of graphene and the Fe cluster. It discusses the key physiochemical properties (e.g. frontier orbital energies and thermodynamic properties) calculated at various levels of theory (e.g. semiempirical, ab initio, density functional theory (DFT) and the periodic DFT) as well as their connections to the reactivity and reaction pathway for the dehalogenation. This paper also reviews the advances in the linear and nonlinear quantitative structure-property relationship models for the dehalogenation kinetics of HOCs and in the mathematical modeling of the dehalogenation processes. Furthermore, prospects of further expansion and exploration of the current research fields are described in this article. Published by Elsevier Ltd.
Augmented multivariate image analysis applied to quantitative structure-activity relationship modeling of the phytotoxicities of benzoxazinone herbicides and related compounds on problematic weeds.

PubMed

Freitas, Mirlaine R; Matias, Stella V B G; Macedo, Renato L G; Freitas, Matheus P; Venturin, Nelson

2013-09-11

Two of major weeds affecting cereal crops worldwide are Avena fatua L. (wild oat) and Lolium rigidum Gaud. (rigid ryegrass). Thus, development of new herbicides against these weeds is required; in line with this, benzoxazinones, their degradation products, and analogues have been shown to be important allelochemicals and natural herbicides. Despite earlier structure-activity studies demonstrating that hydrophobicity (log P) of aminophenoxazines correlates to phytotoxicity, our findings for a series of benzoxazinone derivatives do not show any relationship between phytotoxicity and log P nor with other two usual molecular descriptors. On the other hand, a quantitative structure-activity relationship (QSAR) analysis based on molecular graphs representing structural shape, atomic sizes, and colors to encode other atomic properties performed very accurately for the prediction of phytotoxicities of these compounds against wild oat and rigid ryegrass. Therefore, these QSAR models can be used to estimate the phytotoxicity of new congeners of benzoxazinone herbicides toward A. fatua L. and L. rigidum Gaud.
Quantitative structure toxicity relationships for phenols in isolated rat hepatocytes.

PubMed

Moridani, Majid Y; Siraki, Arno; O'Brien, Peter J

2003-05-06

Quantitative structure toxicity relationship (QSTR) equations were obtained to predict and describe the cytotoxicity of 31 phenols using logLD(50) as a concentration to induce 50% cytotoxicity of isolated rat hepatocytes in 2 h and logP as octanol/water partitioning: logLD(50) (microM)=-0.588(+/-0.059)logP+4.652(+/-0.153) (n=27, r(2)=0.801, s=0.261, P<1 x 10(-9)). Hydroquinone, catechol, 4-nitrophenol, and 2,4-dinitrophenol were outliers for this equation. When the ionization constant pK(a) was considered as a contributing factor a two-parameter QSTR equation was derived: logLD(50) (microM)=-0.595(+/-0.051)logP+0.197(+/-0.029)pK(a)+2.665(+/-0.281) (n=28, r(2)=0.859, s=0.218, P<1 x 10(-6)). Using sigma+, the Brown variation of the Hammet electronic constant, as a contributing parameter, the cytotoxicity of phenols towards hepatocytes were defined by logLD(50) (microM)=-0.594(+/-0.052)logP-0.552(+/-0.085)sigma+ +4.540(+/-0.132) (n=28, r(2)=0.853, s=0.223, P<1 x 10(-6)). Replacing sigma+ with the homolytic bond dissociation energy (BDE) for (X-PhOH+PhO.-->X-PhO.+PhOH) led to logLD(50) (microM)=-0.601(+/-0.066)logP-0.040(+/-0.018)BDE+4.611(+/-0.166) (n=23, r(2)=0.827, s=0.223, P<0.05). Hydroquinone, catechol and 2-nitrophenol were outliers for the above equations. Using redox potential and logP led to a new correlation: logLD(50) (microM)=-0.529(+/-0.135)logP+2.077(+/-0.892)E(p/2)+2.806(+/-0.592) (n=15, r(2)=0.561, s=0.383, P<0.05) with 4-nitrophenol as an outlier. Our findings indicate that phenols with higher lipophilicity, BDE, or sigma+ values or with lower pK(a) and redox potential were more toxic towards hepatocytes. We also showed that a collapse of hepatocyte mitochondrial membrane potential preceded the cytotoxicity of most phenols. Our study indicates that one or a combination of mechanisms; i.e. mitochondrial uncoupling, phenoxy radicals, or phenol metabolism to quinone methides and quinones, contribute to phenol cytotoxicity towards hepatocytes depending on
The Role of Relationship Marketing and SOAR in University Recruiting and Retention

ERIC Educational Resources Information Center

Lange, Tyana

2016-01-01

Institutions of higher education (IHEs) are competing to recruit students in a crowded market with the number of colleges on the increase and the number of high school seniors declining. IHEs are looking for effective ways to recruit students and increase retention and graduation rates. Relationship marketing (RM) is an approach from business that…
The Relationship between Stress, Coping Style, and Academic Satisfaction: A Quantitative Study

ERIC Educational Resources Information Center

Hodge-Windover, Sheila T.

2017-01-01

College students experience a great deal of stress, which is associated with poor health and poor levels of academic satisfaction which can lead to low retention. The purpose of this quantitative correlational study was to investigate how stress and coping style predict academic satisfaction and understand how and if coping style moderates the…
Validity of semi-quantitative scale for brain MRI in unilateral cerebral palsy due to periventricular white matter lesions: Relationship with hand sensorimotor function and structural connectivity.

PubMed

Fiori, Simona; Guzzetta, Andrea; Pannek, Kerstin; Ware, Robert S; Rossi, Giuseppe; Klingels, Katrijn; Feys, Hilde; Coulthard, Alan; Cioni, Giovanni; Rose, Stephen; Boyd, Roslyn N

2015-01-01

To provide first evidence of construct validity of a semi-quantitative scale for brain structural MRI (sqMRI scale) in children with unilateral cerebral palsy (UCP) secondary to periventricular white matter (PWM) lesions, by examining the relationship with hand sensorimotor function and whole brain structural connectivity. Cross-sectional study of 50 children with UCP due to PWM lesions using 3 T (MRI), diffusion MRI and assessment of hand sensorimotor function. We explored the relationship of lobar, hemispheric and global scores on the sqMRI scale, with fractional anisotropy (FA), as a measure of brain white matter microstructure, and with hand sensorimotor measures (Assisting Hand Assessment, AHA; Jebsen-Taylor Test for Hand Function, JTTHF; Melbourne Assessment of Unilateral Upper Limb Function, MUUL; stereognosis; 2-point discrimination). Lobar and hemispheric scores on the sqMRI scale contralateral to the clinical side of hemiplegia correlated with sensorimotor paretic hand function measures and FA of a number of brain structural connections, including connections of brain areas involved in motor control (postcentral, precentral and paracentral gyri in the parietal lobe). More severe lesions correlated with lower sensorimotor performance, with the posterior limb of internal capsule score being the strongest contributor to impaired hand function. The sqMRI scale demonstrates first evidence of construct validity against impaired motor and sensory function measures and brain structural connectivity in a cohort of children with UCP due to PWM lesions. More severe lesions correlated with poorer paretic hand sensorimotor function and impaired structural connectivity in the hemisphere contralateral to the clinical side of hemiplegia. The quantitative structural MRI scoring may be a useful clinical tool for studying brain structure-function relationships but requires further validation in other populations of CP.
Quantitative structure-activity relationships studies of CCR5 inhibitors and toxicity of aromatic compounds using gene expression programming.

PubMed

Shi, Weimin; Zhang, Xiaoya; Shen, Qi

2010-01-01

Quantitative structure-activity relationship (QSAR) study of chemokine receptor 5 (CCR5) binding affinity of substituted 1-(3,3-diphenylpropyl)-piperidinyl amides and ureas and toxicity of aromatic compounds have been performed. The gene expression programming (GEP) was used to select variables and produce nonlinear QSAR models simultaneously using the selected variables. In our GEP implementation, a simple and convenient method was proposed to infer the K-expression from the number of arguments of the function in a gene, without building the expression tree. The results were compared to those obtained by artificial neural network (ANN) and support vector machine (SVM). It has been demonstrated that the GEP is a useful tool for QSAR modeling. Copyright 2009 Elsevier Masson SAS. All rights reserved.
Relationship between Leadership Behaviors of High School Principals and Teacher Retention in Texas

ERIC Educational Resources Information Center

Aiken, Debra L.

2010-01-01

The study investigated the relationship between leadership behaviors of high school principals and teacher retention in Texas. A total of 88 Texas high school principals participated in the survey. Leadership behaviors were measured using the Culturally Adapted Leadership for Inspired Business Excellence and Results (CALIBER) Leadership Assessment…

Relationship of Tech Prep and Dual Credit to College Readiness and Retention

ERIC Educational Resources Information Center

Kim, JoHyun

2014-01-01

This study examined the relationship of tech prep and dual credit to college readiness in reading, writing, and math and retention, measured as total college-level credit hours earned. A sample of 612 high school graduates who enrolled in a community college in two consortia, one in Florida (n = 339) and the other in Oregon…
A Comparative Study on Selective PPAR Modulators through Quantitative Structure-activity Relationship, Pharmacophore and Docking Analyses.

PubMed

Nandy, Ashis; Roy, Kunal; Saha, Achintya

2018-01-01

Metabolic syndrome is a matrix of different metabolic disorders which are the leading cause of death in human beings. Peroxysome proliferated activated receptor (PPAR) is a nuclear receptor involved in metabolism of fats and glucose. In order to explore structural requirements for selective PPAR modulators to control lipid and carbohydrate metabolism, the multi-cheminformatics studies have been performed. In silico modeling studies have been performed on a diverse set of PPAR modulators through quantitative structure-activity relationship (QSAR), pharmacophore mapping and docking studies. It is observed that the presence of an amide fragment (-CONHRPh) has a detrimental effect while an aliphatic ether linkage has a beneficial effect on PPARα modulation. On the other hand, the presence of an amide fragment has a positive effect on PPARδ modulation, but the aliphatic ether linkage and substituted aromatic ring in the molecular scaffold are very much essential for imparting potent and selective PPARγ modulation. Negative ionizable features (i.e. polar fragments) must be present in PPARδ and α modulators, but a hydrophobic feature is the prime requirement for PPARγ modulation. Here, the essential structural features have been explored for selective modulation of each subtype of PPAR in order to design new modulators with improved activity/selectivity. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.
Chromanyl-isoxazolidines as Antibacterial agents: Synthesis, Biological Evaluation, Quantitative Structure Activity Relationship, and Molecular Docking Studies.

PubMed

Singh, Gagandeep; Sharma, Anuradha; Kaur, Harpreet; Ishar, Mohan Paul S

2016-02-01

Regio- and stereoselective 1,3-dipolar cycloadditions of C-(chrom-4-one-3-yl)-N-phenylnitrones (N) with different mono-substituted, disubstituted, and cyclic dipolarophiles were carried out to obtain substituted N-phenyl-3'-(chrom-4-one-3-yl)-isoxazolidines (1-40). All the synthesized compounds were assayed for their in vitro antibacterial activity and display significant inhibitory potential; in particular, compound 32 exhibited good inhibitory activity against Salmonella typhymurium-1 & Salmonella typhymurium-2 with minimum inhibitory concentration value of 1.56 μg/mL and also showed good potential against methicillin-resistant Staphylococcus aureus with minimum inhibitory concentration 3.12 μg/mL. Quantitative structure activity relationship investigations with stepwise multiple linear regression analysis and docking simulation studies have been performed for validation of the observed antibacterial potential of the investigated compounds for determination of the most important parameters regulating antibacterial activities. © 2015 John Wiley & Sons A/S.
Effects of Curriculum and Nonacademic Factors on Undergraduate Electronic Engineering Program Retention

NASA Astrophysics Data System (ADS)

Sulaiman, Munir

Science, technology, engineering, and mathematics (STEM) programs in higher education institutions, particularly engineering programs, face challenges related to recruitment, retention, and graduation rates. The purpose of this study was to determine whether there are significant relationships among students' major preference, academic skills, nonacademic characteristics and perceptions, and retention to year 2 among students in electronic engineering, other STEM, and non STEM majors. The academic skills considered were study habits, intellectual interest, verbal and writing confidence, and academic assistance. The non-academic factors included academic support, family support, financial support, and student social integration into the campus environment. Tinto's theory of retention served as the theoretical framework. The research design was quantitative with a general linear method of analysis using responses to the College Student Inventory (CSI) survey as secondary data to determine the relationships among the independent variables (major and academic and non-academic factors) and dependent variable (retention). Participants were 3,575 first year undergraduate full-time students from three entering classes, 2012 to 2014. Findings suggested that student major and non-academic factors had no effect on student retention, but student study habits and seeking academic assistance were predictors of retention in each of the three groups of majors: engineering, other STEM majors, and nonSTEM majors. Strategies to help increase undergraduate students' study skills and help seeking behaviors may contribute to positive social change at HBCU institutions.
Validity of semi-quantitative scale for brain MRI in unilateral cerebral palsy due to periventricular white matter lesions: Relationship with hand sensorimotor function and structural connectivity

PubMed Central

Fiori, Simona; Guzzetta, Andrea; Pannek, Kerstin; Ware, Robert S.; Rossi, Giuseppe; Klingels, Katrijn; Feys, Hilde; Coulthard, Alan; Cioni, Giovanni; Rose, Stephen; Boyd, Roslyn N.

2015-01-01

Aim To provide first evidence of construct validity of a semi-quantitative scale for brain structural MRI (sqMRI scale) in children with unilateral cerebral palsy (UCP) secondary to periventricular white matter (PWM) lesions, by examining the relationship with hand sensorimotor function and whole brain structural connectivity. Methods Cross-sectional study of 50 children with UCP due to PWM lesions using 3 T (MRI), diffusion MRI and assessment of hand sensorimotor function. We explored the relationship of lobar, hemispheric and global scores on the sqMRI scale, with fractional anisotropy (FA), as a measure of brain white matter microstructure, and with hand sensorimotor measures (Assisting Hand Assessment, AHA; Jebsen–Taylor Test for Hand Function, JTTHF; Melbourne Assessment of Unilateral Upper Limb Function, MUUL; stereognosis; 2-point discrimination). Results Lobar and hemispheric scores on the sqMRI scale contralateral to the clinical side of hemiplegia correlated with sensorimotor paretic hand function measures and FA of a number of brain structural connections, including connections of brain areas involved in motor control (postcentral, precentral and paracentral gyri in the parietal lobe). More severe lesions correlated with lower sensorimotor performance, with the posterior limb of internal capsule score being the strongest contributor to impaired hand function. Conclusion The sqMRI scale demonstrates first evidence of construct validity against impaired motor and sensory function measures and brain structural connectivity in a cohort of children with UCP due to PWM lesions. More severe lesions correlated with poorer paretic hand sensorimotor function and impaired structural connectivity in the hemisphere contralateral to the clinical side of hemiplegia. The quantitative structural MRI scoring may be a useful clinical tool for studying brain structure–function relationships but requires further validation in other populations of CP. PMID:26106533
Leadership Style of Head Teachers of Basic Special Schools as Correlates of Retention of Special Needs Educators in Southern Ghana

ERIC Educational Resources Information Center

Kumedzro, Felix Kwame; Otube, Nelly; Wamunyi, Chomba; Runo, Mary

2016-01-01

The study aimed at establishing relationship between leadership style of head teachers and retention of special education teachers in Southern Ghana. The study was purely quantitative and utilized descriptive correlation design which allowed the researcher to establish the strength and direction of the relationship between the independent variable…
Using spatially variable overstory retention to restore structural and compositional complexity in pine ecosystems

Treesearch

Brian J. Palik; Christel C. Kern; Robert Mitchell; Stephen Pecot

2005-01-01

Increasingly, forest managers incorporate overstory retention into silvicultural prescriptions for forests traditionally managed for single-cohort structure. The ecological benefits of retention may come at the cost of reduced growth of tree regeneration because of competition with residual trees. An important question in retention research, and its application, is how...
Hologram quantitative structure-activity relationship and comparative molecular field analysis studies within a series of tricyclic phthalimide HIV-1 integrase inhibitors.

PubMed

Magalhães, Uiaran de Oliveira; Souza, Alessandra Mendonça Teles de; Albuquerque, Magaly Girão; Brito, Monique Araújo de; Bello, Murilo Lamim; Cabral, Lucio Mendes; Rodrigues, Carlos Rangel

2013-01-01

Acquired immunodeficiency syndrome is a public health problem worldwide caused by the Human immunodeficiency virus (HIV). Treatment with antiretroviral drugs is the best option for viral suppression, reducing morbidity and mortality. However, viral resistance in HIV-1 therapy has been reported. HIV-1 integrase (IN) is an essential enzyme for effective viral replication and an attractive target for the development of new inhibitors. In the study reported here, two- and three-dimensional quantitative structure-activity relationship (2D/3D-QSAR) studies, applying hologram quantitative structure-activity relationship (HQSAR) and comparative molecular field analysis (CoMFA) methods, respectively, were performed on a series of tricyclic phthalimide HIV-1 IN inhibitors. The best HQSAR model (q (2) = 0.802, r (2) = 0.972) was obtained using atoms, bonds, and connectivity as the fragment distinction, a fragment size of 2-5 atoms, hologram length of 61 bins, and six components. The best CoMFA model (q (2) = 0.748, r (2) = 0.974) was obtained with alignment of all atoms of the tricyclic phthalimide moiety (alignment II). The HQSAR contribution map identified that the carbonyl-hydroxy-aromatic nitrogen motif made a positive contribution to the activity of the compounds. Furthermore, CoMFA contour maps suggested that bulky groups in meta and para positions in the phenyl ring would increase the biological activity of this class. The conclusions of this work may lead to a better understanding of HIV-1 IN inhibition and contribute to the design of new and more potent derivatives.
Biomacromolecular quantitative structure-activity relationship (BioQSAR): a proof-of-concept study on the modeling, prediction and interpretation of protein-protein binding affinity.

PubMed

Zhou, Peng; Wang, Congcong; Tian, Feifei; Ren, Yanrong; Yang, Chao; Huang, Jian

2013-01-01

Quantitative structure-activity relationship (QSAR), a regression modeling methodology that establishes statistical correlation between structure feature and apparent behavior for a series of congeneric molecules quantitatively, has been widely used to evaluate the activity, toxicity and property of various small-molecule compounds such as drugs, toxicants and surfactants. However, it is surprising to see that such useful technique has only very limited applications to biomacromolecules, albeit the solved 3D atom-resolution structures of proteins, nucleic acids and their complexes have accumulated rapidly in past decades. Here, we present a proof-of-concept paradigm for the modeling, prediction and interpretation of the binding affinity of 144 sequence-nonredundant, structure-available and affinity-known protein complexes (Kastritis et al. Protein Sci 20:482-491, 2011) using a biomacromolecular QSAR (BioQSAR) scheme. We demonstrate that the modeling performance and predictive power of BioQSAR are comparable to or even better than that of traditional knowledge-based strategies, mechanism-type methods and empirical scoring algorithms, while BioQSAR possesses certain additional features compared to the traditional methods, such as adaptability, interpretability, deep-validation and high-efficiency. The BioQSAR scheme could be readily modified to infer the biological behavior and functions of other biomacromolecules, if their X-ray crystal structures, NMR conformation assemblies or computationally modeled structures are available.
Quantitative MRI in refractory temporal lobe epilepsy: relationship with surgical outcomes

PubMed Central

Bonilha, Leonardo

2015-01-01

Medically intractable temporal lobe epilepsy (TLE) remains a serious health problem. Across treatment centers, up to 40% of patients with TLE will continue to experience persistent postoperative seizures at 2-year follow-up. It is unknown why such a large number of patients continue to experience seizures despite being suitable candidates for resective surgery. Preoperative quantitative MRI techniques may provide useful information on why some patients continue to experience disabling seizures, and may have the potential to develop prognostic markers of surgical outcome. In this article, we provide an overview of how quantitative MRI morphometric and diffusion tensor imaging (DTI) data have improved the understanding of brain structural alterations in patients with refractory TLE. We subsequently review the studies that have applied quantitative structural imaging techniques to identify the neuroanatomical factors that are most strongly related to a poor postoperative prognosis. In summary, quantitative imaging studies strongly suggest that TLE is a disorder affecting a network of neurobiological systems, characterized by multiple and inter-related limbic and extra-limbic network abnormalities. The relationship between brain alterations and postoperative outcome are less consistent, but there is emerging evidence suggesting that seizures are less likely to remit with surgery when presurgical abnormalities are observed in the connectivity supporting brain regions serving as network nodes located outside the resected temporal lobe. Future work, possibly harnessing the potential from multimodal imaging approaches, may further elucidate the etiology of persistent postoperative seizures in patients with refractory TLE. Furthermore, quantitative imaging techniques may be explored to provide individualized measures of postoperative seizure freedom outcome. PMID:25853080
Quantitative structure-activity relationship of the curcumin-related compounds using various regression methods

NASA Astrophysics Data System (ADS)

Khazaei, Ardeshir; Sarmasti, Negin; Seyf, Jaber Yousefi

2016-03-01

Quantitative structure activity relationship were used to study a series of curcumin-related compounds with inhibitory effect on prostate cancer PC-3 cells, pancreas cancer Panc-1 cells, and colon cancer HT-29 cells. Sphere exclusion method was used to split data set in two categories of train and test set. Multiple linear regression, principal component regression and partial least squares were used as the regression methods. In other hand, to investigate the effect of feature selection methods, stepwise, Genetic algorithm, and simulated annealing were used. In two cases (PC-3 cells and Panc-1 cells), the best models were generated by a combination of multiple linear regression and stepwise (PC-3 cells: r2 = 0.86, q2 = 0.82, pred_r2 = 0.93, and r2m (test) = 0.43, Panc-1 cells: r2 = 0.85, q2 = 0.80, pred_r2 = 0.71, and r2m (test) = 0.68). For the HT-29 cells, principal component regression with stepwise (r2 = 0.69, q2 = 0.62, pred_r2 = 0.54, and r2m (test) = 0.41) is the best method. The QSAR study reveals descriptors which have crucial role in the inhibitory property of curcumin-like compounds. 6ChainCount, T_C_C_1, and T_O_O_7 are the most important descriptors that have the greatest effect. With a specific end goal to design and optimization of novel efficient curcumin-related compounds it is useful to introduce heteroatoms such as nitrogen, oxygen, and sulfur atoms in the chemical structure (reduce the contribution of T_C_C_1 descriptor) and increase the contribution of 6ChainCount and T_O_O_7 descriptors. Models can be useful in the better design of some novel curcumin-related compounds that can be used in the treatment of prostate, pancreas, and colon cancers.
Predicting human skin absorption of chemicals: development of a novel quantitative structure activity relationship.

PubMed

Luo, Wen; Medrek, Sarah; Misra, Jatin; Nohynek, Gerhard J

2007-02-01

The objective of this study was to construct and validate a quantitative structure-activity relationship model for skin absorption. Such models are valuable tools for screening and prioritization in safety and efficacy evaluation, and risk assessment of drugs and chemicals. A database of 340 chemicals with percutaneous absorption was assembled. Two models were derived from the training set consisting 306 chemicals (90/10 random split). In addition to the experimental K(ow) values, over 300 2D and 3D atomic and molecular descriptors were analyzed using MDL's QsarIS computer program. Subsequently, the models were validated using both internal (leave-one-out) and external validation (test set) procedures. Using the stepwise regression analysis, three molecular descriptors were determined to have significant statistical correlation with K(p) (R2 = 0.8225): logK(ow), X0 (quantification of both molecular size and the degree of skeletal branching), and SsssCH (count of aromatic carbon groups). In conclusion, two models to estimate skin absorption were developed. When compared to other skin absorption QSAR models in the literature, our model incorporated more chemicals and explored a large number of descriptors. Additionally, our models are reasonably predictive and have met both internal and external statistical validations.
The Relationships among Licensed Nurse Turnover, Retention, and Rehospitalization of Nursing Home Residents

ERIC Educational Resources Information Center

Thomas, Kali S.; Mor, Vincent; Tyler, Denise A.; Hyer, Kathryn

2013-01-01

Purpose: Individuals receiving postacute care in skilled nursing facilities often require complex, skilled care provided by licensed nurses. It is believed that a stable set of nursing personnel is more likely to deliver better care. The purpose of this study was to determine the relationships among licensed nurse retention, turnover, and a 30-day…
Efforts to Improve Undergraduate Student Retention Rates at a Hispanic Serving Institution: Building Collaborative Relationships for the Common Good

ERIC Educational Resources Information Center

Martin, Nancy K.; Meyer, Kristi

2010-01-01

This article describes efforts to improve retention and graduation rates at the University of Texas at San Antonio, a large Hispanic serving institution (HSI). One college within the university is focusing on increasing retention and graduation rates primarily by building relationships and capitalizing on university resources. In addition to…
Quantitative Structure--Activity Relationship (QSAR) for the Oxidation of Trace Organic Contaminants by Sulfate Radical.

PubMed

Xiao, Ruiyang; Ye, Tiantian; Wei, Zongsu; Luo, Shuang; Yang, Zhihui; Spinney, Richard

2015-11-17

The sulfate radical anion (SO4•–) based oxidation of trace organic contaminants (TrOCs) has recently received great attention due to its high reactivity and low selectivity. In this study, a meta-analysis was conducted to better understand the role of functional groups on the reactivity between SO4•– and TrOCs. The results indicate that compounds in which electron transfer and addition channels dominate tend to exhibit a faster second-order rate constants (kSO4•–) than that of H–atom abstraction, corroborating the SO4•– reactivity and mechanisms observed in the individual studies. Then, a quantitative structure activity relationship (QSAR) model was developed using a sequential approach with constitutional, geometrical, electrostatic, and quantum chemical descriptors. Two descriptors, ELUMO and EHOMO energy gap (ELUMO–EHOMO) and the ratio of oxygen atoms to carbon atoms (#O:C), were found to mechanistically and statistically affect kSO4•– to a great extent with the standardized QSAR model: ln kSO4•– = 26.8–3.97 × #O:C – 0.746 × (ELUMO–EHOMO). In addition, the correlation analysis indicates that there is no dominant reaction channel for SO4•– reactions with various structurally diverse compounds. Our QSAR model provides a robust predictive tool for estimating emerging micropollutants removal using SO4•– during wastewater treatment processes.
LANDSCAPE STRUCTURE AND ESTUARINE CONDITION IN THE MID-ATLANTIC REGION OF THE UNITED STATES: I. DEVELOPING QUANTITATIVE RELATIONSHIPS

EPA Science Inventory

In a previously published study, quantitative relationships were developed between landscape metrics and sediment contamination for 25 small estuarine systems within Chesapeake Bay. Nonparametric statistical analysis (rank transformation) was used to develop an empirical relation...
Quantitative structure-activity relationship modeling of rat acute toxicity by oral exposure.

PubMed

Zhu, Hao; Martin, Todd M; Ye, Lin; Sedykh, Alexander; Young, Douglas M; Tropsha, Alexander

2009-12-01

Few quantitative structure-activity relationship (QSAR) studies have successfully modeled large, diverse rodent toxicity end points. In this study, a comprehensive data set of 7385 compounds with their most conservative lethal dose (LD(50)) values has been compiled. A combinatorial QSAR approach has been employed to develop robust and predictive models of acute toxicity in rats caused by oral exposure to chemicals. To enable fair comparison between the predictive power of models generated in this study versus a commercial toxicity predictor, TOPKAT (Toxicity Prediction by Komputer Assisted Technology), a modeling subset of the entire data set was selected that included all 3472 compounds used in TOPKAT's training set. The remaining 3913 compounds, which were not present in the TOPKAT training set, were used as the external validation set. QSAR models of five different types were developed for the modeling set. The prediction accuracy for the external validation set was estimated by determination coefficient R(2) of linear regression between actual and predicted LD(50) values. The use of the applicability domain threshold implemented in most models generally improved the external prediction accuracy but expectedly led to the decrease in chemical space coverage; depending on the applicability domain threshold, R(2) ranged from 0.24 to 0.70. Ultimately, several consensus models were developed by averaging the predicted LD(50) for every compound using all five models. The consensus models afforded higher prediction accuracy for the external validation data set with the higher coverage as compared to individual constituent models. The validated consensus LD(50) models developed in this study can be used as reliable computational predictors of in vivo acute toxicity.
Using a Complexity-Based Perspective to Better Understand the Relationships among Mentoring, School Conflicts, and Novice Retention

ERIC Educational Resources Information Center

Waterman, Sheryn Elaine Spencer

2011-01-01

In this study I used complexity-thinking, ecologically-based sustainable capacity-building, narrative methodology, and pragmatism to explore the relationships among mentoring, conflict, and novice retention. In order to explore these relationships, I constructed stories from my interviews with six mentor-novice dyads in a southeastern 9-12 high…
Academic Advising Structures That Support First-Year Student Success and Retention

ERIC Educational Resources Information Center

McFarlane, Brett Leland

2013-01-01

Academic advising has been touted as a key to student success and retention. Today's academic advising delivery models vary considerably and little is known about the efficiency and effectiveness of these models. The purpose of this study was to determine if there is a relationship between how academic advising is delivered to first-year students…
Quantitative studies on structure-ORAC relationships of anthocyanins from eggplant and radish using 3D-QSAR.

PubMed

Jing, Pu; Zhao, Shujuan; Ruan, Siyu; Sui, Zhongquan; Chen, Lihong; Jiang, Linlei; Qian, Bingjun

2014-02-15

The 3-dimensional quantitative structure activity relationship (3D-QSAR) models were established from 21 anthocyanins based on their oxygen radical absorbing capacity (ORAC) and were applied to predict anthocyanins in eggplant and radish for their ORAC values. The cross-validated q(2)=0.857/0.729, non-cross-validated r(2) = 0.958/0.856, standard error of estimate = 0.153/0.134, and F = 73.267/19.247 were for the best QSAR (CoMFA/CoMSIA) models, where the correlation coefficient r(2)pred = 0.998/0.997 (>0.6) indicated a high predictive ability for each. Additionally, the contour map results suggested that structural characteristics of anthocyanins favourable for the high ORAC. Four anthocyanins from eggplant and radish have been screened based on the QSAR models. Pelargonidin-3-[(6''-p-coumaroyl)-glucosyl(2 → 1)glucoside]-5-(6''-malonyl)-glucoside, delphinidin-3-rutinoside-5-glucoside, and delphinidin-3-[(4''-p-coumaroyl)-rhamnosyl(1 → 6)glucoside]-5-glucoside potential with high ORAC based the QSAR models were isolated and also confirmed for their relative high antioxidant ability, which might attribute to the bulky and/or electron-donating substituent at the 3-position in the C ring or/and hydrogen bond donor group/electron donating group on the R1 position in the B ring. Copyright © 2013 Elsevier Ltd. All rights reserved.

Relationship between Principal Change and Influence Styles: Is There an Impact on Teacher Retention?

ERIC Educational Resources Information Center

Howder, Leslie Johnson

2013-01-01

The purpose of this study was to determine if there is a relationship between principal leadership styles, specifically change and influence styles, and teacher retention in the Low-Country region of South Carolina. Utilizing the Change Style Indicator and Influence Style Indicator, the researcher surveyed 25 principals from Berkeley, Charleston,…
Career satisfaction and retention risk among Wisconsin internists.

PubMed

Giriyappa, Pradeep; Sullivan, Kandis K

2009-09-01

Physician career satisfaction has been studied extensively, but career satisfaction as it relates to retention is less well studied. The objective was to assess the relationship between career satisfaction and retention in primary care internal medicine physicians in Wisconsin. In this descriptive quantitative study, survey data was assessed for correlations between career satisfaction, risk to retention, and demographics. The survey included 1231 primary care internal medicine physicians in the Wisconsin Medical Directory (2007). Responses were measured by career satisfaction variables, and demographics and retention variables for the purpose of correlations and regression analysis. Survey responses included 573 physicians. An additional 85 physicians were disqualified. The final survey group included 1146 physicians for a response rate of 50%. A total of 116 physicians (20.2%) reported anticipating leaving their current position, 84 (14.7%) physicians reported anticipating leaving the career of medicine. Identified at risk for retention were 144 (25.1%) physicians. The lowest career satisfaction scores were reported in the areas of compensation (3.19) and practice (3.42) on a scale of 1 (very dissatisfied) to 5 (very satisfied). The highest correlations to retention were associated with practice, followed by compensation satisfaction. The level of significance for this study was identified as 0.05, and the P-value was 0.000. The study findings reveal a significant risk to the stability of continuity of care for patients, and may cost Wisconsin health care organizations more than $35 million in recruitment costs to replace departing physicians.
Linear solvation energy relationship (LSER) characterization of the normal phase retention mechanism on hypercrosslinked polystyrenes.

PubMed

Wu, Di; Jiang, Ping; Lucy, Charles A

2018-03-30

Linear solvation energy relationships (LSERs) were applied to retention on hypercrosslinked polystyrene on silica (HC-Tol) to elucidate the type and relative importance of molecular interactions between model solutes and the HC-Tol stationary phase. Classical amino phase and another hypercrosslinked phase (5-HGN) were used as reference columns. On both the HC-Tol and amino, polar interactions predominate and contribute to retention. Solute volume V has no impact on retention on the amino column, while V has a slightly negative influence on retention for the HC-Tol column. The differences in coefficient v between the amino and the HC-Tol columns might explain why the HC-Tol is capable of group-type separations. 5-HGN phase has smaller a and b values compared to HC-Tol, which means that 5-HGN is not as basic or acidic in terms of hydrogen bonds as is HC-Tol. This suggests that the hydrogen bonding character of the HC-Tol phase arises from its silica substrate. Copyright © 2018 Elsevier B.V. All rights reserved.
Structural Equation Modeling of Retention and Overage Effects on Dropping Out of School.

ERIC Educational Resources Information Center

Grissom, James B.; Shepard, Lorrie A.

This study addresses the effect that grade retention has on dropping out of school. A structural model was developed to test the effect of grade retention on dropping out while controlling for the effects of other possible mediating variables, especially achievement. This model with slight modifications was applied across four different school…
Synthesis, Spectra, and Theoretical Investigations of 1,3,5-Triazines Compounds as Ultraviolet Rays Absorber Based on Time-Dependent Density Functional Calculations and three-Dimensional Quantitative Structure-Property Relationship.

PubMed

Wang, Xueding; Xu, Yilian; Yang, Lu; Lu, Xiang; Zou, Hao; Yang, Weiqing; Zhang, Yuanyuan; Li, Zicheng; Ma, Menglin

2018-03-01

A series of 1,3,5-triazines were synthesized and their UV absorption properties were tested. The computational chemistry methods were used to construct quantitative structure-property relationship (QSPR), which was used to computer aided design of new 1,3,5-triazines ultraviolet rays absorber compounds. The experimental UV absorption data are in good agreement with those predicted data using the Time-dependent density functional theory (TD-DFT) [B3LYP/6-311 + G(d,p)]. A suitable forecasting model (R > 0.8, P < 0.0001) was revealed. Predictive three-dimensional quantitative structure-property relationship (3D-QSPR) model was established using multifit molecular alignment rule of Sybyl program, which conclusion is consistent with the TD-DFT calculation. The exceptional photostability mechanism of such ultraviolet rays absorber compounds was studied and confirmed as principally banked upon their ability to undergo excited-state deactivation via an ultrafast excited-state proton transfer (ESIPT). The intramolecular hydrogen bond (IMHB) of 1,3,5-triazines compounds is the basis for the excited state proton transfer, which was explored by IR spectroscopy, UV spectra, structural and energetic aspects of different conformers and frontier molecular orbitals analysis.
Design of cinnamaldehyde amino acid Schiff base compounds based on the quantitative structure–activity relationship

Treesearch

Hui Wang; Mingyue Jiang; Shujun Li; Chung-Yun Hse; Chunde Jin; Fangli Sun; Zhuo Li

2017-01-01

Cinnamaldehyde amino acid Schiff base (CAAS) is a new class of safe, bioactive compounds which could be developed as potential antifungal agents for fungal infections. To design new cinnamaldehyde amino acid Schiff base compounds with high bioactivity, the quantitative structureâactivity relationships (QSARs) for CAAS compounds against Aspergillus niger (A. niger) and...
The structure-activity relationship of inhibitors of serotonin uptake and receptor binding

NASA Astrophysics Data System (ADS)

Hansch, Corwin; Caldwell, Jonathan

1991-10-01

An analysis of five different datasets of inhibitors of serotonin uptake has yielded quantitative structure/ activity relationships (QSARs) which delineate the role of steric and hydrophobic properties essential for inhibition by phenylethylamine-type analogues.
Quantitative structure-activity relationships for predicting potential ecological hazard of organic chemicals for use in regulatory risk assessments.

PubMed

Comber, Mike H I; Walker, John D; Watts, Chris; Hermens, Joop

2003-08-01

The use of quantitative structure-activity relationships (QSARs) for deriving the predicted no-effect concentration of discrete organic chemicals for the purposes of conducting a regulatory risk assessment in Europe and the United States is described. In the United States, under the Toxic Substances Control Act (TSCA), the TSCA Interagency Testing Committee and the U.S. Environmental Protection Agency (U.S. EPA) use SARs to estimate the hazards of existing and new chemicals. Within the Existing Substances Regulation in Europe, QSARs may be used for data evaluation, test strategy indications, and the identification and filling of data gaps. To illustrate where and when QSARs may be useful and when their use is more problematic, an example, methyl tertiary-butyl ether (MTBE), is given and the predicted and experimental data are compared. Improvements needed for new QSARs and tools for developing and using QSARs are discussed.
Relationship between Plaque Echo, Thickness and Neovascularization Assessed by Quantitative and Semi-quantitative Contrast-Enhanced Ultrasonography in Different Stenosis Groups.

PubMed

Song, Yan; Feng, Jun; Dang, Ying; Zhao, Chao; Zheng, Jie; Ruan, Litao

2017-12-01

The aim of this study was to determine the relationship between plaque echo, thickness and neovascularization in different stenosis groups using quantitative and semi-quantitative contrast-enhanced ultrasound (CEUS) in patients with carotid atherosclerosis plaque. A total of 224 plaques were divided into mild stenosis (<50%; 135 plaques, 60.27%), moderate stenosis (50%-69%; 39 plaques, 17.41%) and severe stenosis (70%-99%; 50 plaques, 22.32%) groups. Quantitative and semi-quantitative methods were used to assess plaque neovascularization and determine the relationship between plaque echo, thickness and neovascularization. Correlation analysis revealed no relationship of neovascularization with plaque echo in the groups using either quantitative or semi-quantitative methods. Furthermore, there was no correlation of neovascularization with plaque thickness using the semi-quantitative method. The ratio of areas under the curve (RAUC) was negatively correlated with plaque thickness (r = -0.317, p = 0.001) in the mild stenosis group. With the quartile method, plaque thickness of the mild stenosis group was divided into four groups, with significant differences between the 1.5-2.2 mm and ≥3.5 mm groups (p = 0.002), 2.3-2.8 mm and ≥3.5 mm groups (p <0.001) and 2.9-3.4 mm and ≥3.5 mm groups (p <0.001). Both semi-quantitative and quantitative CEUS methods characterizing neovascularization of plaque are equivalent with respect to assessing relationships between neovascularization, echogenicity and thickness. However, the quantitative method could fail for plaque <3.5 mm because of motion artifacts. Copyright © 2017 World Federation for Ultrasound in Medicine and Biology. Published by Elsevier Inc. All rights reserved.
The Impact of Youth-Friendly Structures of Care on Retention Among HIV-Infected Youth

PubMed Central

Yehia, Baligh R.; Gaur, Aditya H.; Rutstein, Richard; Gebo, Kelly; Keruly, Jeanne C.; Moore, Richard D.; Nijhawan, Ank E.; Agwu, Allison L.

2016-01-01

Abstract Limited data exist on how structures of care impact retention among youth living with HIV (YLHIV). We describe the availability of youth-friendly structures of care within HIV Research Network (HIVRN) clinics and examine their association with retention in HIV care. Data from 680 15- to 24-year-old YLHIV receiving care at 7 adult and 5 pediatric clinics in 2011 were included in the analysis. The primary outcome was retention in care, defined as completing ≥2 primary HIV care visits ≥90 days apart in a 12-month period. Sites were surveyed to assess the availability of clinic structures defined a priori as ‘youth-friendly’. Univariate and multivariable logistic regression models assessed structures associated with retention in care. Among 680 YLHIV, 85% were retained. Nearly half (48%) of the 680 YLHIV attended clinics with youth-friendly waiting areas, 36% attended clinics with evening hours, 73% attended clinics with adolescent health-trained providers, 87% could email or text message providers, and 73% could schedule a routine appointment within 2 weeks. Adjusting for demographic and clinical factors, YLHIV were more likely to be retained in care at clinics with a youth-friendly waiting area (AOR 2.47, 95% CI [1.11–5.52]), evening clinic hours (AOR 1.94; 95% CI [1.13–3.33]), and providers with adolescent health training (AOR 1.98; 95% CI [1.01–3.86]). Youth-friendly structures of care impact retention in care among YLHIV. Further investigations are needed to determine how to effectively implement youth-friendly strategies across clinical settings where YLHIV receive care. PMID:26983056
Modeling the reactivities of hydroxyl radical and ozone towards atmospheric organic chemicals using quantitative structure-reactivity relationship approaches.

PubMed

Gupta, Shikha; Basant, Nikita; Mohan, Dinesh; Singh, Kunwar P

2016-07-01

The persistence and the removal of organic chemicals from the atmosphere are largely determined by their reactions with the OH radical and O3. Experimental determinations of the kinetic rate constants of OH and O3 with a large number of chemicals are tedious and resource intensive and development of computational approaches has widely been advocated. Recently, ensemble machine learning (EML) methods have emerged as unbiased tools to establish relationship between independent and dependent variables having a nonlinear dependence. In this study, EML-based, temperature-dependent quantitative structure-reactivity relationship (QSRR) models have been developed for predicting the kinetic rate constants for OH (kOH) and O3 (kO3) reactions with diverse chemicals. Structural diversity of chemicals was evaluated using a Tanimoto similarity index. The generalization and prediction abilities of the constructed models were established through rigorous internal and external validation performed employing statistical checks. In test data, the EML QSRR models yielded correlation (R (2)) of ≥0.91 between the measured and the predicted reactivities. The applicability domains of the constructed models were determined using methods based on descriptors range, Euclidean distance, leverage, and standardization approaches. The prediction accuracies for the higher reactivity compounds were relatively better than those of the low reactivity compounds. Proposed EML QSRR models performed well and outperformed the previous reports. The proposed QSRR models can make predictions of rate constants at different temperatures. The proposed models can be useful tools in predicting the reactivities of chemicals towards OH radical and O3 in the atmosphere.
Structural Consequences of Retention Policies: The Use of Computer Models To Inform Policy.

ERIC Educational Resources Information Center

Morris, Don R.

This paper reports on a longitudinal study of the structural effects of grade retention on dropout rate and percent of graduates qualified. The study drew on computer simulation to explore the effects of retention and how this practice affects dropout rate, the percent of graduates who meet required standards, and enrollment itself. The computer…
Quantitative structure-activity relationship analysis of the pharmacology of para-substituted methcathinone analogues.

PubMed

Bonano, J S; Banks, M L; Kolanos, R; Sakloth, F; Barnier, M L; Glennon, R A; Cozzi, N V; Partilla, J S; Baumann, M H; Negus, S S

2015-05-01

Methcathinone (MCAT) is a potent monoamine releaser and parent compound to emerging drugs of abuse including mephedrone (4-CH3 MCAT), the para-methyl analogue of MCAT. This study examined quantitative structure-activity relationships (QSAR) for MCAT and six para-substituted MCAT analogues on (a) in vitro potency to promote monoamine release via dopamine and serotonin transporters (DAT and SERT, respectively), and (b) in vivo modulation of intracranial self-stimulation (ICSS), a behavioural procedure used to evaluate abuse potential. Neurochemical and behavioural effects were correlated with steric (Es ), electronic (σp ) and lipophilic (πp ) parameters of the para substituents. For neurochemical studies, drug effects on monoamine release through DAT and SERT were evaluated in rat brain synaptosomes. For behavioural studies, drug effects were tested in male Sprague-Dawley rats implanted with electrodes targeting the medial forebrain bundle and trained to lever-press for electrical brain stimulation. MCAT and all six para-substituted analogues increased monoamine release via DAT and SERT and dose- and time-dependently modulated ICSS. In vitro selectivity for DAT versus SERT correlated with in vivo efficacy to produce abuse-related ICSS facilitation. In addition, the Es values of the para substituents correlated with both selectivity for DAT versus SERT and magnitude of ICSS facilitation. Selectivity for DAT versus SERT in vitro is a key determinant of abuse-related ICSS facilitation by these MCAT analogues, and steric aspects of the para substituent of the MCAT scaffold (indicated by Es ) are key determinants of this selectivity. © 2014 The British Pharmacological Society.
Application of quantitative structure activity relationship (QSAR) models to predict ozone toxicity in the lung.

PubMed

Kafoury, Ramzi M; Huang, Ming-Ju

2005-08-01

The sequence of events leading to ozone-induced airway inflammation is not well known. To elucidate the molecular and cellular events underlying ozone toxicity in the lung, we hypothesized that lipid ozonation products (LOPs) generated by the reaction of ozone with unsaturated fatty acids in the epithelial lining fluid and cell membranes play a key role in mediating ozone-induced airway inflammation. To test our hypothesis, we ozonized 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphatidylcholine (POPC) and generated LOPs. Confluent human bronchial epithelial cells were exposed to the derivatives of ozonized POPC-9-oxononanoyl, 9-hydroxy-9-hydroperoxynonanoyl, and 8-(5-octyl-1,2,4-trioxolan-3-yl-)octanoyl-at a concentration of 10 muM, and the activity of phospholipases A2 (PLA2), C (PLC), and D (PLD) was measured (1, 0.5, and 1 h, respectively). Quantitative structure-activity relationship (QSAR) models were utilized to predict the biological activity of LOPs in airway epithelial cells. The QSAR results showed a strong correlation between experimental and computed activity (r = 0.97, 0.98, 0.99, for PLA2, PLC, and PLD, respectively). The results indicate that QSAR models can be utilized to predict the biological activity of the various ozone-derived LOP species in the lung. Copyright 2005 Wiley Periodicals, Inc.
How Money Helps Keep Students in College: The Relationship between Family Finances, Merit-Based Aid, and Retention in Higher Education

ERIC Educational Resources Information Center

Olbrecht, Alexandre M.; Romano, Christopher; Teigen, Jeremy

2016-01-01

In this paper, we leverage detailed, individual-level student data to understand the relationships between family finances, merit-based aid, and first-year student retention. With three cohorts of student data that comprise family financial status, institutional merit scholarships, and many of the other known correlates of student retention, we…
Structure-biodegradability relationship of nonylphenol isomers during biological wastewater treatment process.

PubMed

Hao, Ruixia; Li, Jianbing; Zhou, Yuwen; Cheng, Shuiyuan; Zhang, Yi

2009-05-01

The relationship between nonylphenol (NP) isomer structure and its biodegradability within the wastewater treatment process of sequencing batch reactor (SBR) was investigated. The GC-MS method was used for detecting the NP isomers existing in the SBR influent, activated sludge and effluent. Fifteen NP isomers were detected in the influent, with significant biodegradability variations being observed among these isomers. It was found that the NP isomers associated with retention time of 10.553, 10.646, 10.774, and 10.906 min in the GC-MS analysis showed higher biodegradability, while the isomers with retention time of 10.475, 10.800, and 10.857 min illustrated lower biodegradability. Through analyzing the mass spectrograms, the chemical structures of four selected NP isomers in the wastewater were further deduced. The higher correlation coefficients of 0.9421 and 0.9085 were observed between the NP isomer biodegradation rates and the molecular connectivity indexes with the order of two and four, respectively. Such correlation analysis indicated that a more complex side branch structure (such as a larger side carbon-chain branch or more branches in the nonyl) of NP isomer would lead to lower biodegradability, and a longer nonyl chain of the isomer would result in a higher biodegradability.
Quantitative structure-activity relationship and molecular docking of artemisinin derivatives to vascular endothelial growth factor receptor 1.

PubMed

Saeed, Mohamed E M; Kadioglu, Onat; Seo, Ean-Jeong; Greten, Henry Johannes; Brenk, Ruth; Efferth, Thomas

2015-04-01

The antimalarial drug artemisinin has been shown to exert anticancer activity through anti-angiogenic effects. For further drug development, it may be useful to have derivatives with improved anti-angiogenic properties. We performed molecular docking of 52 artemisinin derivatives to vascular endothelial growth factor receptors (VEGFR1, VEGFR2), and VEGFA ligand using Autodock4 and AutodockTools-1.5.7.rc1 using the Lamarckian genetic algorithm. Quantitative structure-activity relationship (QSAR) analyses of the compounds prepared by Corina Molecular Networks were performed using the Molecular Operating Environment MOE 2012.10. A statistically significant inverse relationship was obtained between in silico binding energies to VEGFR1 and anti-angiogenic activity in vivo of a test-set of artemisinin derivatives (R=-0.843; p=0.035). This served as a control experiment to validate molecular docking predicting anti-angiogenc effects. Furthermore, 52 artemisinin derivatives were docked to VEGFR1 and in selected examples also to VEGFR2 and VEGFA. Higher binding affinities were calculated for receptors than for the ligand. The best binding affinities to VEGFR1 were found for an artemisinin dimer, 10-dihydroartemisinyl-2-propylpentanoate, and dihydroartemisinin α-hemisuccinate sodium salt. QSAR analyses revealed significant relationships between VEGFR1 binding energies and defined molecular descriptors of 35 artemisinins assigned to the training set (R=0.0848, p<0.0001) and 17 derivatives assigned to the test set (R=0.761, p<0.001). Molecular docking and QSAR calculations can be used to identify novel artemisinin derivatives with anti-angiogenic effects. Copyright© 2015 International Institute of Anticancer Research (Dr. John G. Delinassios), All rights reserved.
Quantitative structure activity relationships from optimised ab initio bond lengths: steroid binding affinity and antibacterial activity of nitrofuran derivatives

NASA Astrophysics Data System (ADS)

Smith, P. J.; Popelier, P. L. A.

2004-02-01

The present day abundance of cheap computing power enables the use of quantum chemical ab initio data in Quantitative Structure-Activity Relationships (QSARs). Optimised bond lengths are a new such class of descriptors, which we have successfully used previously in representing electronic effects in medicinal and ecological QSARs (enzyme inhibitory activity, hydrolysis rate constants and pKas). Here we use AM1 and HF/3-21G* bond lengths in conjunction with Partial Least Squares (PLS) and a Genetic Algorithm (GA) to predict the Corticosteroid-Binding Globulin (CBG) binding activity of the classic steroid data set, and the antibacterial activity of nitrofuran derivatives. The current procedure, which does not require molecular alignment, produces good r2 and q2 values. Moreover, it highlights regions in the common steroid skeleton deemed relevant to the active regions of the steroids and nitrofuran derivatives.
New Insights Toward Quantitative Relationships between Lignin Reactivity to Monomers and Their Structural Characteristics.

PubMed

Ma, Ruoshui; Zhang, Xiumei; Wang, Yi; Zhang, Xiao

2018-04-27

The heterogeneous and complex structural characteristics of lignin present a significant challenge to predict its processability (e.g. depolymerization, modifications etc) to valuable products. This study provides a detailed characterization and comparison of structural properties of seven representative biorefinery lignin samples derived from forest and agricultural residues, which were subjected to representative pretreatment methods. A range of wet chemistry and spectroscopy methods were applied to determine specific lignin structural characteristics such as functional groups, inter-unit linkages and peak molecular weight. In parallel, oxidative depolymerization of these lignin samples to either monomeric phenolic compounds or dicarboxylic acids were conducted, and the product yields were quantified. Based on these results (lignin structural characteristics and monomer yields), we demonstrated for the first time to apply multiple-variable linear estimations (MVLE) approach using R statistics to gain insight toward a quantitative correlation between lignin structural properties and their conversion reactivity toward oxidative depolymerization to monomers. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Retention of Economics Principles by Undergraduates on Alternative Curricular Structures

ERIC Educational Resources Information Center

Johnson, Daniel K. N.; Lybecker, Kristina M.; Taylor, Corrine H.

2011-01-01

The authors investigated whether the curricular structure of an economics course (semester, trimester, or compressed block schedule) has an effect on an undergraduate's subsequent retention of course material, while controlling for other relevant differences. They tested separately for theoretical or process comprehension and for graphical…

Learning Communities in Undergraduate STEM Education: A Quantitative Analysis of how Sense of Community Influences Retention of Students

NASA Astrophysics Data System (ADS)

Archie, T.; Newman, P.

2012-12-01

Countless programs are aimed at retaining first year college students in their majors and at their institutions. Additionally, first year students in STEM majors are retained at lower rates, than non-STEM majors. Previous research has shown that students who leave the institution are not as academically and socially integrated into the campus community than students who persist at an institution. Residential learning communities can be thought of as a retention tool by enhancing the academic and social integration of their participants. Academic integration has historically been measured by academic success as indicated by GPA, while social integration has been more difficult to measure. We adapted the Sense of Community Index (SCI) as a measure of social integration. Sense of community (SOC) has been defined as ''a feeling that members have of belonging, a feeling that members matter to one another and to the group, and a shared faith that members' needs will be met through their commitment to be together''. This quantitative study examines sense of community as a means of social integration and explores the relationship between learning communities, students' sense of community, and their intent to persist at a large public university and within their current major. An online survey of 60 first-year college students in a Natural Resources College, examined the relationships between learning community participation, sense of community, and student retention. A logistic regression of sense of community was very effective in predicting students' intent to stay or leave the institution. Structural equation models showed that sense of community was strongly positively related to a students' intent to stay or leave the institution for non-learning community participants, but not for learning community participants. We hypothesized that learning community participants sense of community needs would be more fully met than non-learning community participants. Learning
The Relationship between Quantitative and Qualitative Measures of Writing Skills.

ERIC Educational Resources Information Center

Howerton, Mary Lou P.; And Others

The relationships of quantitative measures of writing skills to overall writing quality as measured by the E.T.S. Composition Evaluation Scale (CES) were examined. Quantitative measures included indices of language productivity, vocabulary diversity, spelling, and syntactic maturity. Power of specific indices to account for variation in overall…
Factors Influencing Retention of Gen Y and Non-Gen Y Teachers Working at International Schools in Asia

ERIC Educational Resources Information Center

Fong, Hoi Wah Benny

2018-01-01

Quantitative studies on international-school teacher retention are few, especially studies that differentiate between Gen Y and non-Gen Y teachers. This article reports on the findings of a study that examined the relationship of job satisfaction factors to the likelihood of contract renewal by international-school teachers. Results from the study…
Structured Opportunities: Exploring the Social and Academic Benefits for Peer Mentors in Retention Programs

ERIC Educational Resources Information Center

Kiyama, Judy Marquez; Luca, Sandra Guillen

2014-01-01

Informed by the experiences of former peer mentors, this qualitative study examines the structure of opportunity of a university retention program. Extending the concept of social capital, the study investigates the experiences of students who served as peer mentors, and how their involvement in the retention program has influenced their social…
High resolution light microscopic evaluation of boar semen quality sperm cytoplasmic droplet retention in relationship with boar fertility parameters.

PubMed

Lovercamp, K W; Safranski, T J; Fischer, K A; Manandhar, G; Sutovsky, M; Herring, W; Sutovsky, P

2007-01-01

The purpose of this study was to investigate the relationship between fertility and quantitative measures of boar semen quality, including various patterns of sperm cytoplasmic droplet (CD) retention, as determined by high power differential interference contrast (DIC) microscopy. A total of 116 ejaculates were collected from a nucleus herd of 18 Large White boars over an eight month period. Semen quality parameters were analyzed for each ejaculate by calculating the percentage of normal spermatozoa, spermatozoa possessing a CD in the proximal, distal, or distal midpiece reflex position, total spermatozoa with an attached cytoplasmic droplet, spermatozoa with non-CD related aberrations and total spermatozoa with abnormalities. Of the 116 ejaculates received, 71 ejaculates from 13 boars had corresponding fertility data from single-sire inseminations of multiparous sows. The fertility data included farrowing rate (FR) and total number born (TNB). The monthly FR encompassed one month before and one month after the date of semen collection. Detection of differences for fertility and semen quality parameters was performed by separating the boars into either an above-average or below-average group based on the mean FR (74.01 +/- 1.43%) or TNB (12.34 +/- 0.17) for the study. For FR, the boars in the below-average group had a significantly lower percentage of normal spermatozoa and significantly higher percentage of spermatozoa possessing distal CDs, total attached CDs and total abnormalities compared to the boars in the above-average group. Conversely, for TNB there were no significant differences between the above- and below-average groups for the semen quality parameters. These data suggest that the attached CD may negatively affect FR, but not TNB. The detection of relationships between the boar fertility parameters and the retention of the sperm CD after ejaculation, document the advantage of high power DIC microscopy in conventional semen evaluation.
Quantitative structure-activity relationship analysis of substituted arylazo pyridone dyes in photocatalytic system: Experimental and theoretical study.

PubMed

Dostanić, J; Lončarević, D; Zlatar, M; Vlahović, F; Jovanović, D M

2016-10-05

A series of arylazo pyridone dyes was synthesized by changing the type of the substituent group in the diazo moiety, ranging from strong electron-donating to strong electron-withdrawing groups. The structural and electronic properties of the investigated dyes was calculated at the M062X/6-31+G(d,p) level of theory. The observed good linear correlations between atomic charges and Hammett σp constants provided a basis to discuss the transmission of electronic substituent effects through a dye framework. The reactivity of synthesized dyes was tested through their decolorization efficiency in TiO2 photocatalytic system (Degussa P-25). Quantitative structure-activity relationship analysis revealed a strong correlation between reactivity of investigated dyes and Hammett substituent constants. The reaction was facilitated by electron-withdrawing groups, and retarded by electron-donating ones. Quantum mechanical calculations was used in order to describe the mechanism of the photocatalytic oxidation reactions of investigated dyes and interpret their reactivities within the framework of the Density Functional Theory (DFT). According to DFT based reactivity descriptors, i.e. Fukui functions and local softness, the active site moves from azo nitrogen atom linked to benzene ring to pyridone carbon atom linked to azo bond, going from dyes with electron-donating groups to dyes with electron-withdrawing groups. Copyright © 2016 Elsevier B.V. All rights reserved.
Retention modelling of polychlorinated biphenyls in comprehensive two-dimensional gas chromatography.

PubMed

D'Archivio, Angelo Antonio; Incani, Angela; Ruggieri, Fabrizio

2011-01-01

In this paper, we use a quantitative structure-retention relationship (QSRR) method to predict the retention times of polychlorinated biphenyls (PCBs) in comprehensive two-dimensional gas chromatography (GC×GC). We analyse the GC×GC retention data taken from the literature by comparing predictive capability of different regression methods. The various models are generated using 70 out of 209 PCB congeners in the calibration stage, while their predictive performance is evaluated on the remaining 139 compounds. The two-dimensional chromatogram is initially estimated by separately modelling retention times of PCBs in the first and in the second column ((1) t (R) and (2) t (R), respectively). In particular, multilinear regression (MLR) combined with genetic algorithm (GA) variable selection is performed to extract two small subsets of predictors for (1) t (R) and (2) t (R) from a large set of theoretical molecular descriptors provided by the popular software Dragon, which after removal of highly correlated or almost constant variables consists of 237 structure-related quantities. Based on GA-MLR analysis, a four-dimensional and a five-dimensional relationship modelling (1) t (R) and (2) t (R), respectively, are identified. Single-response partial least square (PLS-1) regression is alternatively applied to independently model (1) t (R) and (2) t (R) without the need for preliminary GA variable selection. Further, we explore the possibility of predicting the two-dimensional chromatogram of PCBs in a single calibration procedure by using a two-response PLS (PLS-2) model or a feed-forward artificial neural network (ANN) with two output neurons. In the first case, regression is carried out on the full set of 237 descriptors, while the variables previously selected by GA-MLR are initially considered as ANN inputs and subjected to a sensitivity analysis to remove the redundant ones. Results show PLS-1 regression exhibits a noticeably better descriptive and predictive
Novel word retention in bilingual and monolingual speakers

PubMed Central

Kan, Pui Fong; Sadagopan, Neeraja

2014-01-01

The goal of this research was to examine word retention in bilinguals and monolinguals. Long-term word retention is an essential part of vocabulary learning. Previous studies have documented that bilinguals outperform monolinguals in terms of retrieving newly-exposed words. Yet, little is known about whether or to what extent bilinguals are different from monolinguals in word retention. Participants were 30 English-speaking monolingual adults and 30 bilingual adults who speak Spanish as a home language and learned English as a second language during childhood. In a previous study (Kan et al., 2014), the participants were exposed to the target novel words in English, Spanish, and Cantonese. In this current study, word retention was measured a week after the fast mapping task. No exposures were given during the one-week interval. Results showed that bilinguals and monolinguals retain a similar number of words. However, participants produced more words in English than in either Spanish or Cantonese. Correlation analyses revealed that language knowledge plays a role in the relationships between fast mapping and word retention. Specifically, within- and across-language relationships between bilinguals' fast mapping and word retention were found in Spanish and English, by contrast, within-language relationships between monolinguals' fast mapping and word retention were found in English and across-language relationships between their fast mapping and word retention performance in English and Cantonese. Similarly, bilinguals differed from monolinguals in the relationships among the word retention scores in three languages. Significant correlations were found among bilinguals' retention scores. However, no such correlations were found among monolinguals' retention scores. The overall findings suggest that bilinguals' language experience and language knowledge most likely contribute to how they learn and retain new words. PMID:25324789
Novel word retention in bilingual and monolingual speakers.

PubMed

Kan, Pui Fong; Sadagopan, Neeraja

2014-01-01

The goal of this research was to examine word retention in bilinguals and monolinguals. Long-term word retention is an essential part of vocabulary learning. Previous studies have documented that bilinguals outperform monolinguals in terms of retrieving newly-exposed words. Yet, little is known about whether or to what extent bilinguals are different from monolinguals in word retention. Participants were 30 English-speaking monolingual adults and 30 bilingual adults who speak Spanish as a home language and learned English as a second language during childhood. In a previous study (Kan et al., 2014), the participants were exposed to the target novel words in English, Spanish, and Cantonese. In this current study, word retention was measured a week after the fast mapping task. No exposures were given during the one-week interval. Results showed that bilinguals and monolinguals retain a similar number of words. However, participants produced more words in English than in either Spanish or Cantonese. Correlation analyses revealed that language knowledge plays a role in the relationships between fast mapping and word retention. Specifically, within- and across-language relationships between bilinguals' fast mapping and word retention were found in Spanish and English, by contrast, within-language relationships between monolinguals' fast mapping and word retention were found in English and across-language relationships between their fast mapping and word retention performance in English and Cantonese. Similarly, bilinguals differed from monolinguals in the relationships among the word retention scores in three languages. Significant correlations were found among bilinguals' retention scores. However, no such correlations were found among monolinguals' retention scores. The overall findings suggest that bilinguals' language experience and language knowledge most likely contribute to how they learn and retain new words.
A Job Retention Model for Individuals with Mental Retardation

ERIC Educational Resources Information Center

Fornes, Sandra

2006-01-01

This structured literature review examines the literature and addresses issues of job retention for adult workers with moderate to mild mental retardation (MR), investigating the relationships between work-related social behaviors, self-determination, person-job congruency of individuals with MR, and their job performance and job satisfaction with…
An Examination of the Relationship between Retention, Grade Point Average, and Developmental Characteristics of College Freshmen.

ERIC Educational Resources Information Center

Allbritten, Bill

Attrition, which averages 40 percent among college freshmen, has been associated with academic skills, career decision making, psychological characteristics, and institutional climate. To determine the self-perceived developmental characteristics of college freshmen and the relationship of those characteristics to retention and grade point average…
Synthetic cannabinoids: In silico prediction of the cannabinoid receptor 1 affinity by a quantitative structure-activity relationship model.

PubMed

Paulke, Alexander; Proschak, Ewgenij; Sommer, Kai; Achenbach, Janosch; Wunder, Cora; Toennes, Stefan W

2016-03-14

The number of new synthetic psychoactive compounds increase steadily. Among the group of these psychoactive compounds, the synthetic cannabinoids (SCBs) are most popular and serve as a substitute of herbal cannabis. More than 600 of these substances already exist. For some SCBs the in vitro cannabinoid receptor 1 (CB1) affinity is known, but for the majority it is unknown. A quantitative structure-activity relationship (QSAR) model was developed, which allows the determination of the SCBs affinity to CB1 (expressed as binding constant (Ki)) without reference substances. The chemically advance template search descriptor was used for vector representation of the compound structures. The similarity between two molecules was calculated using the Feature-Pair Distribution Similarity. The Ki values were calculated using the Inverse Distance Weighting method. The prediction model was validated using a cross validation procedure. The predicted Ki values of some new SCBs were in a range between 20 (considerably higher affinity to CB1 than THC) to 468 (considerably lower affinity to CB1 than THC). The present QSAR model can serve as a simple, fast and cheap tool to get a first hint of the biological activity of new synthetic cannabinoids or of other new psychoactive compounds. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
Emotional intelligence and clinical performance/retention of nursing students

PubMed Central

Marvos, Chelsea; Hale, Frankie B.

2015-01-01

Objective: This exploratory, quantitative, descriptive study was undertaken to explore the relationship between clinical performance and anticipated retention in nursing students. Methods: After approval by the university's Human Subjects Committee, a sample of 104 nursing students were recruited for this study, which involved testing with a valid and reliable emotional intelligence (EI) instrument and a self-report survey of clinical competencies. Results: Statistical analysis revealed that although the group average for total EI score and the 6 score subsets were in the average range, approximately 30% of the individual total EI scores and 30% of two branch scores, identifying emotions correctly and understanding emotions, fell in the less than average range. This data, as well as the analysis of correlation with clinical self-report scores, suggest recommendations applicable to educators of clinical nursing students. Conclusions: Registered nurses make-up the largest segment of the ever-growing healthcare workforce. Yet, retention of new graduates has historically been a challenge for the profession. Given the projected employment growth in nursing, it is important to identify factors which correlate with high levels of performance and job retention among nurses. There is preliminary evidence that EI a nontraditional intelligence measure relates positively not only with retention of clinical staff nurses, but with overall clinical performance as well. PMID:27981096
Emotional intelligence and clinical performance/retention of nursing students.

PubMed

Marvos, Chelsea; Hale, Frankie B

2015-01-01

This exploratory, quantitative, descriptive study was undertaken to explore the relationship between clinical performance and anticipated retention in nursing students. After approval by the university's Human Subjects Committee, a sample of 104 nursing students were recruited for this study, which involved testing with a valid and reliable emotional intelligence (EI) instrument and a self-report survey of clinical competencies. Statistical analysis revealed that although the group average for total EI score and the 6 score subsets were in the average range, approximately 30% of the individual total EI scores and 30% of two branch scores, identifying emotions correctly and understanding emotions, fell in the less than average range. This data, as well as the analysis of correlation with clinical self-report scores, suggest recommendations applicable to educators of clinical nursing students. Registered nurses make-up the largest segment of the ever-growing healthcare workforce. Yet, retention of new graduates has historically been a challenge for the profession. Given the projected employment growth in nursing, it is important to identify factors which correlate with high levels of performance and job retention among nurses. There is preliminary evidence that EI a nontraditional intelligence measure relates positively not only with retention of clinical staff nurses, but with overall clinical performance as well.
Nanoporous Cyanate Ester Resins: Structure-Gas Transport Property Relationships

NASA Astrophysics Data System (ADS)

Gusakova, Kristina; Fainleib, Alexander; Espuche, Eliane; Grigoryeva, Olga; Starostenko, Olga; Gouanve, Fabrice; Boiteux, Gisèle; Saiter, Jean-Marc; Grande, Daniel

2017-04-01

This contribution addresses the relationships between the structure and gas transport properties of nanoporous thermostable cyanate ester resins (CERs) derived from polycyclotrimerization of 1,1'-bis(4-cyanatophenyl)ethane in the presence of 30 or 50 wt% of inert high-boiling temperature porogens (i.e., dimethyl- or dibutyl phthalates), followed by their quantitative removal. The nanopores in the films obtained were generated via a chemically induced phase separation route with further porogen extraction from the densely crosslinked CERs. To ensure a total desorption of the porogen moieties from the networks, an additional short-term thermal annealing at 250 °C was performed. The structure and morphology of such nanoporous CER-based films were investigated by FTIR and SEM techniques, respectively. Further, the gas transport properties of CER films were analyzed after the different processing steps, and relationships between the material structure and the main gas transport parameters were established.
The Relationship of Clinical Nurses' Perceptions of Structural and Psychological Empowerment and Engagement on Their Unit.

PubMed

DiNapoli, Jean Marie; O'Flaherty, Deirdre; Musil, Carol; Clavelle, Joanne T; Fitzpatrick, Joyce J

2016-02-01

The purpose of this study was to describe relationships between structural empowerment, psychological empowerment, and engagement among clinical nurses. Empowerment and engagement are key drivers of retention and quality in healthcare. Creating an empowering culture and an engaged staff supports initiatives that are essential for positive work environments. A survey of 280 nurses in a national conference was conducted using the Conditions of Work Effectiveness, Psychological Empowerment Instrument, and the Utrecht Work Engagement Scale. Pearson correlation coefficients and multiple regression analysis were used to determine relationships between demographic data and study variables. Overall, nurses had high perceptions of structural empowerment and psychological empowerment and were moderately engaged. Also, significant positive relationships were found between the key study variables. Results show positive correlations between empowerment and perceived engagement among clinical nurses.
Motivation and retention of health workers in Ghana's district hospitals: addressing the critical issues.

PubMed

Adzei, Francis A; Atinga, Roger A

2012-01-01

This study seeks to undertake a systematic review to consolidate existing empirical evidence on the impact of financial and non-financial incentives on motivation and retention of health workers in Ghana's district hospitals. The study employed a purely quantitative design with a sample of 285 health workers from ten district hospitals in four regions of Ghana. A stepwise regression model was used in the analysis. The study found that financial incentives significantly influence motivation and intention to remain in the district hospital. Further, of the four factor model of the non-financial incentives, only three (leadership skill and supervision, opportunities for continuing professional development and availability of infrastructure and resources) were predictors of motivation and retention. A major limitation of the study is that the sample of health workers was biased towards nurses (n = 160; 56.1 percent). This is explained by their large presence in remote districts in Ghana. A qualitative approach could enrich the findings by bringing out the many complex views of health workers regarding issues of motivation and retention, since quantitative studies are better applied to establish causal relationships. The findings suggest that appropriate legislations backing salary supplements, commitment-based bonus payments with a set of internal regulations and leadership with sound managerial qualities are required to pursue workforce retention in district hospitals.
Retention of Emergency Care Knowledge.

ERIC Educational Resources Information Center

Burckes, Mardie E.; Shao, Kung Ping Pam

1984-01-01

Data on the emergency care knowledge of college students were measured by a pretest, posttest, and retention test. A high relationship was found between students' posttest scores and retention test scores. Findings are discussed. (Author/DF)
Quantitative structure-activity relationship study of P2X7 receptor inhibitors using combination of principal component analysis and artificial intelligence methods.

PubMed

Ahmadi, Mehdi; Shahlaei, Mohsen

2015-01-01

P2X7 antagonist activity for a set of 49 molecules of the P2X7 receptor antagonists, derivatives of purine, was modeled with the aid of chemometric and artificial intelligence techniques. The activity of these compounds was estimated by means of combination of principal component analysis (PCA), as a well-known data reduction method, genetic algorithm (GA), as a variable selection technique, and artificial neural network (ANN), as a non-linear modeling method. First, a linear regression, combined with PCA, (principal component regression) was operated to model the structure-activity relationships, and afterwards a combination of PCA and ANN algorithm was employed to accurately predict the biological activity of the P2X7 antagonist. PCA preserves as much of the information as possible contained in the original data set. Seven most important PC's to the studied activity were selected as the inputs of ANN box by an efficient variable selection method, GA. The best computational neural network model was a fully-connected, feed-forward model with 7-7-1 architecture. The developed ANN model was fully evaluated by different validation techniques, including internal and external validation, and chemical applicability domain. All validations showed that the constructed quantitative structure-activity relationship model suggested is robust and satisfactory.
The relationship between vulnerable attachment style, psychopathology, drug abuse, and retention in treatment among methadone maintenance treatment patients.

PubMed

Potik, David; Peles, Einat; Abramsohn, Yahli; Adelson, Miriam; Schreiber, Shaul

2014-01-01

The relationship between vulnerable attachment style, psychopathology, drug abuse, and retention in treatment among patients in methadone maintenance treatment (MMT) was examined by the Vulnerable Attachment Style Questionnaire (VASQ), the Symptom Checklist-90 (SCL-90), and drug abuse urine tests. After six years, retention in treatment and repeated urine test results were studied. Patients with vulnerable attachment style (a high VASQ score) had higher rates of drug abuse and higher psychopathology levels compared to patients with secure attachment style, especially on the interpersonal sensitivity, anxiety, hostility, phobic anxiety, and paranoid ideation scales. Drug abstinence at baseline was related to retention in treatment and to higher rates of drug abstinence after six years in MMT, whereas a vulnerable attachment style could not predict drug abstinence and retention in treatment. Clinical Implications concerning treatment of drug abusing populations and methodological issues concerning the VASQ's subscales are also discussed.

A novel two-step hierarchical quantitative structure-activity relationship modeling work flow for predicting acute toxicity of chemicals in rodents.

PubMed

Zhu, Hao; Ye, Lin; Richard, Ann; Golbraikh, Alexander; Wright, Fred A; Rusyn, Ivan; Tropsha, Alexander

2009-08-01

Accurate prediction of in vivo toxicity from in vitro testing is a challenging problem. Large public-private consortia have been formed with the goal of improving chemical safety assessment by the means of high-throughput screening. A wealth of available biological data requires new computational approaches to link chemical structure, in vitro data, and potential adverse health effects. A database containing experimental cytotoxicity values for in vitro half-maximal inhibitory concentration (IC(50)) and in vivo rodent median lethal dose (LD(50)) for more than 300 chemicals was compiled by Zentralstelle zur Erfassung und Bewertung von Ersatz- und Ergaenzungsmethoden zum Tierversuch (ZEBET; National Center for Documentation and Evaluation of Alternative Methods to Animal Experiments). The application of conventional quantitative structure-activity relationship (QSAR) modeling approaches to predict mouse or rat acute LD(50) values from chemical descriptors of ZEBET compounds yielded no statistically significant models. The analysis of these data showed no significant correlation between IC(50) and LD(50). However, a linear IC(50) versus LD(50) correlation could be established for a fraction of compounds. To capitalize on this observation, we developed a novel two-step modeling approach as follows. First, all chemicals are partitioned into two groups based on the relationship between IC(50) and LD(50) values: One group comprises compounds with linear IC(50) versus LD(50) relationships, and another group comprises the remaining compounds. Second, we built conventional binary classification QSAR models to predict the group affiliation based on chemical descriptors only. Third, we developed k-nearest neighbor continuous QSAR models for each subclass to predict LD(50) values from chemical descriptors. All models were extensively validated using special protocols. The novelty of this modeling approach is that it uses the relationships between in vivo and in vitro data only
The impact of staff case manager-case management supervisor relationship on job satisfaction and retention of RN case managers.

PubMed

Hogan, Tierney D

2005-01-01

A positive relationship between staff RN case managers and their case management supervisor significantly impacts job satisfaction and retention in case managers. Literature review supports the premise that staff need to trust their supervisor and that there is a connection between this trust and job satisfaction. Staff case managers need to have a voice at work and feel empowered, and a supervisor's leadership style can influence job satisfaction and retention in their staff.
Quantitative structure activity relationship and risk analysis of some pesticides in the goat milk.

PubMed

Muhammad, Faqir; Awais, Mian Muhammad; Akhtar, Masood; Anwar, Muhammad Irfan

2013-01-04

The detection and quantification of different pesticides in the goat milk samples collected from different localities of Faisalabad, Pakistan was performed by HPLC using solid phase microextraction. The analysis showed that about 50% milk samples were contaminated with pesticides. The mean±SEM levels (ppm) of cyhalothrin, endosulfan, chlorpyrifos and cypermethrin were 0.34±0.007, 0.063±0.002, 0.034±0.002 and 0.092±0.002, respectively; whereas, methyl parathion was not detected in any of the analyzed samples. Quantitative structure activity relationship (QSAR) models were suggested to predict the residues of unknown pesticides in the goat milk using their known physicochemical characteristics including molecular weight (MW), melting point (MP), and log octanol to water partition coefficient (Ko/w) in relation to the characteristics such as pH, % fat, specific gravity and refractive index of goat milk. The analysis revealed good correlation coefficient (R2 = 0.985) for goat QSAR model. The coefficients for Ko/w and refractive index for the studied pesticides were higher in goat milk. This suggests that these are better determinants for pesticide residue prediction in the milk of these animals. Based upon the determined pesticide residues and their provisional tolerable daily intakes, risk analysis was also conducted which showed that daily intake levels of pesticide residues including cyhalothrin, chlorpyrifos and cypermethrin in present study are 2.68, 5.19 and 2.71 times higher, respectively in the goat milk. This intake of pesticide contaminated milk might pose health hazards to humans in this locality.
Quantitative structure activity relationship and risk analysis of some pesticides in the goat milk

PubMed Central

2013-01-01

The detection and quantification of different pesticides in the goat milk samples collected from different localities of Faisalabad, Pakistan was performed by HPLC using solid phase microextraction. The analysis showed that about 50% milk samples were contaminated with pesticides. The mean±SEM levels (ppm) of cyhalothrin, endosulfan, chlorpyrifos and cypermethrin were 0.34±0.007, 0.063±0.002, 0.034±0.002 and 0.092±0.002, respectively; whereas, methyl parathion was not detected in any of the analyzed samples. Quantitative structure activity relationship (QSAR) models were suggested to predict the residues of unknown pesticides in the goat milk using their known physicochemical characteristics including molecular weight (MW), melting point (MP), and log octanol to water partition coefficient (Ko/w) in relation to the characteristics such as pH, % fat, specific gravity and refractive index of goat milk. The analysis revealed good correlation coefficient (R2 = 0.985) for goat QSAR model. The coefficients for Ko/w and refractive index for the studied pesticides were higher in goat milk. This suggests that these are better determinants for pesticide residue prediction in the milk of these animals. Based upon the determined pesticide residues and their provisional tolerable daily intakes, risk analysis was also conducted which showed that daily intake levels of pesticide residues including cyhalothrin, chlorpyrifos and cypermethrin in present study are 2.68, 5.19 and 2.71 times higher, respectively in the goat milk. This intake of pesticide contaminated milk might pose health hazards to humans in this locality. PMID:23369514
Quantitative structure activity relationship studies of sulfamide derivatives as carbonic anhydrase inhibitor: as antiglaucoma agents.

PubMed

Kumar, Surendra; Singh, Vineet; Tiwari, Meena

2007-07-01

Selective inhibition of ciliary process enzyme i.e. Carbonic Anhydrase-II is an excellent approach in reducing elevated intraocular pressure, thus treating glaucoma. Due to characteristic physicochemical properties of sulphonamide (Inhibition of Carbonic Anhydrase), they are clinically effective against glaucoma. But the non-specificity of sulphonamide derivatives to isozyme, leads to a range of side effects. Presently, the absence of comparative studies related to the binding of the sulphonamides as inhibitors to CA isozymes limits their use. In this paper we have represented "Three Dimensional Quantitative Structure Activity Relationship" study to characterize structural features of Sulfamide derivative [RR'NSO(2)NH(2)] as inhibitors, that are required for selective binding of carbonic anhydrase isozymes (CAI and CAII). In the analysis, stepwise multiple linear regression was performed using physiochemical parameters as independent variable and CA-I and CA-II inhibitory activity as dependent variable, respectively. The best multiparametric QSAR model obtained for CA-I inhibitory activity shows good statistical significance (r= 0.9714) and predictability (Q(2)=0.8921), involving the Electronic descriptors viz. Highest Occupied Molecular Orbital, Lowest Unoccupied Molecular Orbital and Steric descriptors viz. Principal moment of Inertia at X axis. Similarly, CA-II inhibitory activity also shows good statistical significance (r=0.9644) and predictability (Q(2)=0.8699) involving aforementioned descriptors. The predictive power of the model was successfully tested externally using a set of six compounds as test set for CA-I inhibitory activity and a set of seven compounds in case of CA-II inhibitory activity with good predictive squared correlation coefficient, r(2)(pred)=0.6016 and 0.7662, respectively. Overview of analysis favours substituents with high electronegativity and less bulk at R and R' positions of the parent nucleus, provides a basis to design new
Quantitative structure-activity relationships of the antimalarial agent artemisinin and some of its derivatives - a DFT approach.

PubMed

Rajkhowa, Sanchaita; Hussain, Iftikar; Hazarika, Kalyan K; Sarmah, Pubalee; Deka, Ramesh Chandra

2013-09-01

Artemisinin form the most important class of antimalarial agents currently available, and is a unique sesquiterpene peroxide occurring as a constituent of Artemisia annua. Artemisinin is effectively used in the treatment of drug-resistant Plasmodium falciparum and because of its rapid clearance of cerebral malaria, many clinically useful semisynthetic drugs for severe and complicated malaria have been developed. However, one of the major disadvantages of using artemisinins is their poor solubility either in oil or water and therefore, in order to overcome this difficulty many derivatives of artemisinin were prepared. A comparative study on the chemical reactivity of artemisinin and some of its derivatives is performed using density functional theory (DFT) calculations. DFT based global and local reactivity descriptors, such as hardness, chemical potential, electrophilicity index, Fukui function, and local philicity calculated at the optimized geometries are used to investigate the usefulness of these descriptors for understanding the reactive nature and reactive sites of the molecules. Multiple regression analysis is applied to build up a quantitative structure-activity relationship (QSAR) model based on the DFT based descriptors against the chloroquine-resistant, mefloquine-sensitive Plasmodium falciparum W-2 clone.
Comparative pharmacodynamic analysis of imidazoline compounds using rat model of ocular mydriasis with a test of quantitative structure-activity relationships.

PubMed

Raczak-Gutknecht, Joanna; Nasal, Antoni; Frąckowiak, Teresa; Kornicka, Anita; Sączewski, Franciszek; Wawrzyniak, Renata; Kubik, Łukasz; Kaliszan, Roman

2017-09-10

Imidazol(in)e derivatives, having the chemical structure similar to clonidine, exert diverse pharmacological activities connected with their interactions with alpha2-adrenergic receptors, e.g. hypotension, bradycardia, sedation as well as antinociceptive, anxiolytic, antiarrhythmic, muscle relaxant and mydriatic effects. The mechanism of pupillary dilation observed after systemic administration of imidazol(in)es to rats, mice and cats depends on the stimulation of postsynaptic alpha2-adrenoceptors within the brain. It was proved that the central nervous system (CNS)-localized I1-imidazoline receptors are not engaged in those effects. It appeared interesting to analyze the CNS-mediated pharmacodynamics of imidazole(in)e agents in terms of their chromatographic and calculation chemistry-derived parameters. In the present study a systematic determination and comparative pharmacometric analysis of mydriatic effects in rats were performed on a series of 20 imidazol(in)e agents, composed of the well-known drugs and of the substances used in experimental pharmacology. The eye pupil dilatory activities of the compounds were assessed in anesthetized Wistar rats according to the established Koss method. Among twenty imidazol(in)e derivatives studied, 18 produced diverse dose-dependent mydriatic effects. In the quantitative structure-activity relationships (QSAR) analysis, the pharmacological data (half maximum mydriatic effect - ED 50 in μmol/kg) were considered along with the structural parameters of the agents from molecular modeling. The theoretically calculated lipophilicity parameters, CLOGP, of imidazol(in)es, as well as their lipophilicity parameters from HPLC, logk w , were also considered. The attempts to derive statistically significant QSAR equations for a full series of the agents under study were unsuccessful. However, for a subgroup of eight apparently structurally related imidazol(in)es a significant relationship between log(1/ED 50 ) and logk w values was
Bryophyte species richness on retention aspens recovers in time but community structure does not.

PubMed

Oldén, Anna; Ovaskainen, Otso; Kotiaho, Janne S; Laaka-Lindberg, Sanna; Halme, Panu

2014-01-01

Green-tree retention is a forest management method in which some living trees are left on a logged area. The aim is to offer 'lifeboats' to support species immediately after logging and to provide microhabitats during and after forest re-establishment. Several studies have shown immediate decline in bryophyte diversity after retention logging and thus questioned the effectiveness of this method, but longer term studies are lacking. Here we studied the epiphytic bryophytes on European aspen (Populus tremula L.) retention trees along a 30-year chronosequence. We compared the bryophyte flora of 102 'retention aspens' on 14 differently aged retention sites with 102 'conservation aspens' on 14 differently aged conservation sites. We used a Bayesian community-level modelling approach to estimate the changes in bryophyte species richness, abundance (area covered) and community structure during 30 years after logging. Using the fitted model, we estimated that two years after logging both species richness and abundance of bryophytes declined, but during the following 20-30 years both recovered to the level of conservation aspens. However, logging-induced changes in bryophyte community structure did not fully recover over the same time period. Liverwort species showed some or low potential to benefit from lifeboating and high potential to re-colonise as time since logging increases. Most moss species responded similarly, but two cushion-forming mosses benefited from the logging disturbance while several weft- or mat-forming mosses declined and did not re-colonise in 20-30 years. We conclude that retention trees do not function as equally effective lifeboats for all bryophyte species but are successful in providing suitable habitats for many species in the long-term. To be most effective, retention cuts should be located adjacent to conservation sites, which may function as sources of re-colonisation and support the populations of species that require old-growth forests.
Resolving structural influences on water-retention properties of alluvial deposits

USGS Publications Warehouse

Winfield, K.A.; Nimmo, J.R.; Izbicki, J.A.; Martin, P.M.

2006-01-01

With the goal of improving property-transfer model (PTM) predictions of unsaturated hydraulic properties, we investigated the influence of sedimentary structure, defined as particle arrangement during deposition, on laboratory-measured water retention (water content vs. potential [??(??)]) of 10 undisturbed core samples from alluvial deposits in the western Mojave Desert, California. The samples were classified as having fluvial or debris-flow structure based on observed stratification and measured spread of particle-size distribution. The ??(??) data were fit with the Rossi-Nimmo junction model, representing water retention with three parameters: the maximum water content (??max), the ??-scaling parameter (??o), and the shape parameter (??). We examined trends between these hydraulic parameters and bulk physical properties, both textural - geometric mean, Mg, and geometric standard deviation, ??g, of particle diameter - and structural - bulk density, ??b, the fraction of unfilled pore space at natural saturation, Ae, and porosity-based randomness index, ??s, defined as the excess of total porosity over 0.3. Structural parameters ??s and Ae were greater for fluvial samples, indicating greater structural pore space and a possibly broader pore-size distribution associated with a more systematic arrangement of particles. Multiple linear regression analysis and Mallow's Cp statistic identified combinations of textural and structural parameters for the most useful predictive models: for ??max, including Ae, ??s, and ??g, and for both ??o and ??, including only textural parameters, although use of Ae can somewhat improve ??o predictions. Textural properties can explain most of the sample-to-sample variation in ??(??) independent of deposit type, but inclusion of the simple structural indicators Ae and ??s can improve PTM predictions, especially for the wettest part of the ??(??) curve. ?? Soil Science Society of America.
Design and prediction of new acetylcholinesterase inhibitor via quantitative structure activity relationship of huprines derivatives.

PubMed

Zhang, Shuqun; Hou, Bo; Yang, Huaiyu; Zuo, Zhili

2016-05-01

Acetylcholinesterase (AChE) is an important enzyme in the pathogenesis of Alzheimer's disease (AD). Comparative quantitative structure-activity relationship (QSAR) analyses on some huprines inhibitors against AChE were carried out using comparative molecular field analysis (CoMFA), comparative molecular similarity indices analysis (CoMSIA), and hologram QSAR (HQSAR) methods. Three highly predictive QSAR models were constructed successfully based on the training set. The CoMFA, CoMSIA, and HQSAR models have values of r (2) = 0.988, q (2) = 0.757, ONC = 6; r (2) = 0.966, q (2) = 0.645, ONC = 5; and r (2) = 0.957, q (2) = 0.736, ONC = 6. The predictabilities were validated using an external test sets, and the predictive r (2) values obtained by the three models were 0.984, 0.973, and 0.783, respectively. The analysis was performed by combining the CoMFA and CoMSIA field distributions with the active sites of the AChE to further understand the vital interactions between huprines and the protease. On the basis of the QSAR study, 14 new potent molecules have been designed and six of them are predicted to be more active than the best active compound 24 described in the literature. The final QSAR models could be helpful in design and development of novel active AChE inhibitors.
Overview of data and conceptual approaches for derivation of quantitative structure-activity relationships for ecotoxicological effects of organic chemicals.

PubMed

Bradbury, Steven P; Russom, Christine L; Ankley, Gerald T; Schultz, T Wayne; Walker, John D

2003-08-01

The use of quantitative structure-activity relationships (QSARs) in assessing potential toxic effects of organic chemicals on aquatic organisms continues to evolve as computational efficiency and toxicological understanding advance. With the ever-increasing production of new chemicals, and the need to optimize resources to assess thousands of existing chemicals in commerce, regulatory agencies have turned to QSARs as essential tools to help prioritize tiered risk assessments when empirical data are not available to evaluate toxicological effects. Progress in designing scientifically credible QSARs is intimately associated with the development of empirically derived databases of well-defined and quantified toxicity endpoints, which are based on a strategic evaluation of diverse sets of chemical structures, modes of toxic action, and species. This review provides a brief overview of four databases created for the purpose of developing QSARs for estimating toxicity of chemicals to aquatic organisms. The evolution of QSARs based initially on general chemical classification schemes, to models founded on modes of toxic action that range from nonspecific partitioning into hydrophobic cellular membranes to receptor-mediated mechanisms is summarized. Finally, an overview of expert systems that integrate chemical-specific mode of action classification and associated QSAR selection for estimating potential toxicological effects of organic chemicals is presented.
In silico prediction of nematic transition temperature for liquid crystals using quantitative structure-property relationship approaches.

PubMed

Fatemi, Mohammad Hossein; Ghorbanzad'e, Mehdi

2009-11-01

Quantitative structure-property relationship models for the prediction of the nematic transition temperature (T (N)) were developed by using multilinear regression analysis and a feedforward artificial neural network (ANN). A collection of 42 thermotropic liquid crystals was chosen as the data set. The data set was divided into three sets: for training, and an internal and external test set. Training and internal test sets were used for ANN model development, and the external test set was used for evaluation of the predictive power of the model. In order to build the models, a set of six descriptors were selected by the best multilinear regression procedure of the CODESSA program. These descriptors were: atomic charge weighted partial negatively charged surface area, relative negative charged surface area, polarity parameter/square distance, minimum most negative atomic partial charge, molecular volume, and the A component of moment of inertia, which encode geometrical and electronic characteristics of molecules. These descriptors were used as inputs to ANN. The optimized ANN model had 6:6:1 topology. The standard errors in the calculation of T (N) for the training, internal, and external test sets using the ANN model were 1.012, 4.910, and 4.070, respectively. To further evaluate the ANN model, a crossvalidation test was performed, which produced the statistic Q (2) = 0.9796 and standard deviation of 2.67 based on predicted residual sum of square. Also, the diversity test was performed to ensure the model's stability and prove its predictive capability. The obtained results reveal the suitability of ANN for the prediction of T (N) for liquid crystals using molecular structural descriptors.
Quantitative structure-activity relationship for the partition coefficient of hydrophobic compounds between silicone oil and air.

PubMed

Qu, Yanfei; Ma, Yongwen; Wan, Jinquan; Wang, Yan

2018-06-01

The silicon oil-air partition coefficients (K SiO/A ) of hydrophobic compounds are vital parameters for applying silicone oil as non-aqueous-phase liquid in partitioning bioreactors. Due to the limited number of K SiO/A values determined by experiment for hydrophobic compounds, there is an urgent need to model the K SiO/A values for unknown chemicals. In the present study, we developed a universal quantitative structure-activity relationship (QSAR) model using a sequential approach with macro-constitutional and micromolecular descriptors for silicone oil-air partition coefficients (K SiO/A ) of hydrophobic compounds with large structural variance. The geometry optimization and vibrational frequencies of each chemical were calculated using the hybrid density functional theory at the B3LYP/6-311G** level. Several quantum chemical parameters that reflect various intermolecular interactions as well as hydrophobicity were selected to develop QSAR model. The result indicates that a regression model derived from logK SiO/A , the number of non-hydrogen atoms (#nonHatoms) and energy gap of E LUMO and E HOMO (E LUMO -E HOMO ) could explain the partitioning mechanism of hydrophobic compounds between silicone oil and air. The correlation coefficient R 2 of the model is 0.922, and the internal and external validation coefficient, Q 2 LOO and Q 2 ext , are 0.91 and 0.89 respectively, implying that the model has satisfactory goodness-of-fit, robustness, and predictive ability and thus provides a robust predictive tool to estimate the logK SiO/A values for chemicals in application domain. The applicability domain of the model was visualized by the Williams plot.
Sexual dimorphism in stature (SDS), jealousy and mate retention.

PubMed

Brewer, Gayle; Riley, Charlene

2010-10-02

Previous research has investigated the manner in which absolute height impacts on jealousy and mate retention. Although relative height is also important, little information exists about the potential influence of sexual dimorphism in stature (SDS) within established relationships. The current study investigated the relationship between SDS and the satisfaction, jealousy and mate retention behaviors reported by men and women. Heterosexual men (n = 98) and women (n = 102) completed a questionnaire. Men in high SDS relationships reported the lowest levels of cognitive and behavioral jealousy, although the impact of SDS on relationship satisfaction was less clear. SDS was not associated with the overall use of mate retention strategies; SDS did however affect the use of three specific strategies (vigilance, monopolization of time, love and care). SDS did not affect women's relationship satisfaction, jealousy (cognitive, behavioral, or emotional) or the use of mate retention strategies (with the exception of resource display).
Learning Quantitative Sequence-Function Relationships from Massively Parallel Experiments

NASA Astrophysics Data System (ADS)

Atwal, Gurinder S.; Kinney, Justin B.

2016-03-01

A fundamental aspect of biological information processing is the ubiquity of sequence-function relationships—functions that map the sequence of DNA, RNA, or protein to a biochemically relevant activity. Most sequence-function relationships in biology are quantitative, but only recently have experimental techniques for effectively measuring these relationships been developed. The advent of such "massively parallel" experiments presents an exciting opportunity for the concepts and methods of statistical physics to inform the study of biological systems. After reviewing these recent experimental advances, we focus on the problem of how to infer parametric models of sequence-function relationships from the data produced by these experiments. Specifically, we retrace and extend recent theoretical work showing that inference based on mutual information, not the standard likelihood-based approach, is often necessary for accurately learning the parameters of these models. Closely connected with this result is the emergence of "diffeomorphic modes"—directions in parameter space that are far less constrained by data than likelihood-based inference would suggest. Analogous to Goldstone modes in physics, diffeomorphic modes arise from an arbitrarily broken symmetry of the inference problem. An analytically tractable model of a massively parallel experiment is then described, providing an explicit demonstration of these fundamental aspects of statistical inference. This paper concludes with an outlook on the theoretical and computational challenges currently facing studies of quantitative sequence-function relationships.
The renal excretion and retention of macromolecules: The chemical structure effect.

PubMed

Rypácek, F; Drobník, J; Chmelar, V; Kálal, J

1982-01-01

Five derivatives of polyaspartamide were used as macromolecular models to study the effect of chemical structure of macromolecules on their renal excretion and retention. The parent polymer was formed solely by N(2-hydroxyethyl)aspartamide units (I) and in its derivatives about 20% of 2-hydroxyethyl groups were randomly replaced by either n-butyl- (II), 2(4-hydroxyphenyl)ethyl- (III, N- dimethylamino propyl- (IV) or the aspartamide unit was modified to free aspartic acid carboxyl (V). The rate of clearance from the serum, the deposition in the kidney tissue in comparison with the deposition in reticuloendothelial system organs-liver and spleen, as well as tissue and cellular localisation of deposits were studied on rabbits and mice taking advantage of fluorescence labelling. The clearance of macromolecular models from the serum compartment by the glomerular filtration is mainly molecular weight controlled, while the retention of macromolecules possessing the same molecular weight by the kidney tubular epithelium is strongly affected chemical modification. About thirty and hundred times higher retentions due to reabsorption in proximal tubule were found with macromolecular models II and III respectively.
Bryophyte Species Richness on Retention Aspens Recovers in Time but Community Structure Does Not

PubMed Central

Oldén, Anna; Ovaskainen, Otso; Kotiaho, Janne S.; Laaka-Lindberg, Sanna; Halme, Panu

2014-01-01

Green-tree retention is a forest management method in which some living trees are left on a logged area. The aim is to offer ‘lifeboats’ to support species immediately after logging and to provide microhabitats during and after forest re-establishment. Several studies have shown immediate decline in bryophyte diversity after retention logging and thus questioned the effectiveness of this method, but longer term studies are lacking. Here we studied the epiphytic bryophytes on European aspen (Populus tremula L.) retention trees along a 30-year chronosequence. We compared the bryophyte flora of 102 ‘retention aspens’ on 14 differently aged retention sites with 102 ‘conservation aspens’ on 14 differently aged conservation sites. We used a Bayesian community-level modelling approach to estimate the changes in bryophyte species richness, abundance (area covered) and community structure during 30 years after logging. Using the fitted model, we estimated that two years after logging both species richness and abundance of bryophytes declined, but during the following 20–30 years both recovered to the level of conservation aspens. However, logging-induced changes in bryophyte community structure did not fully recover over the same time period. Liverwort species showed some or low potential to benefit from lifeboating and high potential to re-colonise as time since logging increases. Most moss species responded similarly, but two cushion-forming mosses benefited from the logging disturbance while several weft- or mat-forming mosses declined and did not re-colonise in 20–30 years. We conclude that retention trees do not function as equally effective lifeboats for all bryophyte species but are successful in providing suitable habitats for many species in the long-term. To be most effective, retention cuts should be located adjacent to conservation sites, which may function as sources of re-colonisation and support the populations of species that require old
A quantitative structure-activity relationship to predict efficacy of granular activated carbon adsorption to control emerging contaminants.

PubMed

Kennicutt, A R; Morkowchuk, L; Krein, M; Breneman, C M; Kilduff, J E

2016-08-01

A quantitative structure-activity relationship was developed to predict the efficacy of carbon adsorption as a control technology for endocrine-disrupting compounds, pharmaceuticals, and components of personal care products, as a tool for water quality professionals to protect public health. Here, we expand previous work to investigate a broad spectrum of molecular descriptors including subdivided surface areas, adjacency and distance matrix descriptors, electrostatic partial charges, potential energy descriptors, conformation-dependent charge descriptors, and Transferable Atom Equivalent (TAE) descriptors that characterize the regional electronic properties of molecules. We compare the efficacy of linear (Partial Least Squares) and non-linear (Support Vector Machine) machine learning methods to describe a broad chemical space and produce a user-friendly model. We employ cross-validation, y-scrambling, and external validation for quality control. The recommended Support Vector Machine model trained on 95 compounds having 23 descriptors offered a good balance between good performance statistics, low error, and low probability of over-fitting while describing a wide range of chemical features. The cross-validated model using a log-uptake (qe) response calculated at an aqueous equilibrium concentration (Ce) of 1 μM described the training dataset with an r(2) of 0.932, had a cross-validated r(2) of 0.833, and an average residual of 0.14 log units.
On the Development and Use of Large Chemical Similarity Networks, Informatics Best Practices and Novel Chemical Descriptors Towards Materials Quantitative Structure Property Relationships

NASA Astrophysics Data System (ADS)

Krein, Michael

After decades of development and use in a variety of application areas, Quantitative Structure Property Relationships (QSPRs) and related descriptor-based statistical learning methods have achieved a level of infamy due to their misuse. The field is rife with past examples of overtrained models, overoptimistic performance assessment, and outright cheating in the form of explicitly removing data to fit models. These actions do not serve the community well, nor are they beneficial to future predictions based on established models. In practice, in order to select combinations of descriptors and machine learning methods that might work best, one must consider the nature and size of the training and test datasets, be aware of existing hypotheses about the data, and resist the temptation to bias structure representation and modeling to explicitly fit the hypotheses. The definition and application of these best practices is important for obtaining actionable modeling outcomes, and for setting user expectations of modeling accuracy when predicting the endpoint values of unknowns. A wide variety of statistical learning approaches, descriptor types, and model validation strategies are explored herein, with the goals of helping end users understand the factors involved in creating and using QSPR models effectively, and to better understand relationships within the data, especially by looking at the problem space from multiple perspectives. Molecular relationships are commonly envisioned in a continuous high-dimensional space of numerical descriptors, referred to as chemistry space. Descriptor and similarity metric choice influence the partitioning of this space into regions corresponding to local structural similarity. These regions, known as domains of applicability, are most likely to be successfully modeled by a QSPR. In Chapter 2, the network topology and scaling relationships of several chemistry spaces are thoroughly investigated. Chemistry spaces studied include the
4-Aminoquinolines Active against Chloroquine-Resistant Plasmodium falciparum: Basis of Antiparasite Activity and Quantitative Structure-Activity Relationship Analyses▿

PubMed Central

Hocart, Simon J.; Liu, Huayin; Deng, Haiyan; De, Dibyendu; Krogstad, Frances M.; Krogstad, Donald J.

2011-01-01

Chloroquine (CQ) is a safe and economical 4-aminoquinoline (AQ) antimalarial. However, its value has been severely compromised by the increasing prevalence of CQ resistance. This study examined 108 AQs, including 68 newly synthesized compounds. Of these 108 AQs, 32 (30%) were active only against CQ-susceptible Plasmodium falciparum strains and 59 (55%) were active against both CQ-susceptible and CQ-resistant P. falciparum strains (50% inhibitory concentrations [IC50s], ≤25 nM). All AQs active against both CQ-susceptible and CQ-resistant P. falciparum strains shared four structural features: (i) an AQ ring without alkyl substitution, (ii) a halogen at position 7 (Cl, Br, or I but not F), (iii) a protonatable nitrogen at position 1, and (iv) a second protonatable nitrogen at the end of the side chain distal from the point of attachment to the AQ ring via the nitrogen at position 4. For activity against CQ-resistant parasites, side chain lengths of ≤3 or ≥10 carbons were necessary but not sufficient; they were identified as essential factors by visual comparison of 2-dimensional (2-D) structures in relation to the antiparasite activities of the AQs and were confirmed by computer-based 3-D comparisons and differential contour plots of activity against P. falciparum. The advantage of the method reported here (refinement of quantitative structure-activity relationship [QSAR] descriptors by random assignment of compounds to multiple training and test sets) is that it retains QSAR descriptors according to their abilities to predict the activities of unknown test compounds rather than according to how well they fit the activities of the compounds in the training sets. PMID:21383099

Relationships Among Job Structural Attributes, Retention, Task Descriptions, Aptitudes, and Work Values. Technical Report No. 3.

ERIC Educational Resources Information Center

Barrett, Gerald V.; And Others

The report describes field studies involving nonsupervisory Naval maintenance and monitoring electronics personnel. The studies' results indicated that Naval retention was related to a number of individual and job attributes. Extended Naval tenure was associated with lower verbal and clerical aptitudes (Naval Test Battery); higher levels of…
Mentoring--a staff retention tool.

PubMed

Kanaskie, Mary Louise

2006-01-01

Staff retention presents a common challenge for hospitals nationwide. Mentorship programs have been explored as one method of creating environments that promote staff retention. Successful achievement of nurse competencies identified in the Synergy Model for Patient Care can best be achieved in an environment that encourages and facilitates mentoring. Mentoring relationships in critical care provide the ongoing interactions, coaching, teaching, and role modeling to facilitate nurses' progression along this continuum. Mentoring relationships offer support and professional development for nurses at all levels within an organization as well as an optimistic outlook for the nursing profession.
The effects of a combination of text structure awareness and graphic postorganizers on recall and retention of science knowledge

NASA Astrophysics Data System (ADS)

Spiegel, George F., Jr.; Barufaldi, James P.

The purpose of this study was to determine the effectiveness of a self-regulated strategy on immediate recall and retention of science knowledge in community-college anatomy and physiology students who participated in a 14-hour (8 weeks) study skills class. The class emphasized the recognition of five common science textbook text structures (cause and effect, classification, enumeration, generalization, and sequence) and the construction of graphic postorganizers of the text structures. A pretest, two immediate posttests, and a retention posttest were used to measure recall and retention. Results indicated that on immediate posttests students who actively constructed graphic postorganizers of the test structure recalled significantly more content than did the control students who simply underlined, reread, or highlighted. On a 3-week retention posttest, those students in the study skills class retained significantly more of the material studied than did the control group of students.
Quantitative criticism of literary relationships

PubMed Central

Dexter, Joseph P.; Katz, Theodore; Tripuraneni, Nilesh; Dasgupta, Tathagata; Kannan, Ajay; Brofos, James A.; Bonilla Lopez, Jorge A.; Schroeder, Lea A.; Casarez, Adriana; Rabinovich, Maxim; Haimson Lushkov, Ayelet; Chaudhuri, Pramit

2017-01-01

Authors often convey meaning by referring to or imitating prior works of literature, a process that creates complex networks of literary relationships (“intertextuality”) and contributes to cultural evolution. In this paper, we use techniques from stylometry and machine learning to address subjective literary critical questions about Latin literature, a corpus marked by an extraordinary concentration of intertextuality. Our work, which we term “quantitative criticism,” focuses on case studies involving two influential Roman authors, the playwright Seneca and the historian Livy. We find that four plays related to but distinct from Seneca’s main writings are differentiated from the rest of the corpus by subtle but important stylistic features. We offer literary interpretations of the significance of these anomalies, providing quantitative data in support of hypotheses about the use of unusual formal features and the interplay between sound and meaning. The second part of the paper describes a machine-learning approach to the identification and analysis of citational material that Livy loosely appropriated from earlier sources. We extend our approach to map the stylistic topography of Latin prose, identifying the writings of Caesar and his near-contemporary Livy as an inflection point in the development of Latin prose style. In total, our results reflect the integration of computational and humanistic methods to investigate a diverse range of literary questions. PMID:28373557
Quantitative criticism of literary relationships.

PubMed

Dexter, Joseph P; Katz, Theodore; Tripuraneni, Nilesh; Dasgupta, Tathagata; Kannan, Ajay; Brofos, James A; Bonilla Lopez, Jorge A; Schroeder, Lea A; Casarez, Adriana; Rabinovich, Maxim; Haimson Lushkov, Ayelet; Chaudhuri, Pramit

2017-04-18

Authors often convey meaning by referring to or imitating prior works of literature, a process that creates complex networks of literary relationships ("intertextuality") and contributes to cultural evolution. In this paper, we use techniques from stylometry and machine learning to address subjective literary critical questions about Latin literature, a corpus marked by an extraordinary concentration of intertextuality. Our work, which we term "quantitative criticism," focuses on case studies involving two influential Roman authors, the playwright Seneca and the historian Livy. We find that four plays related to but distinct from Seneca's main writings are differentiated from the rest of the corpus by subtle but important stylistic features. We offer literary interpretations of the significance of these anomalies, providing quantitative data in support of hypotheses about the use of unusual formal features and the interplay between sound and meaning. The second part of the paper describes a machine-learning approach to the identification and analysis of citational material that Livy loosely appropriated from earlier sources. We extend our approach to map the stylistic topography of Latin prose, identifying the writings of Caesar and his near-contemporary Livy as an inflection point in the development of Latin prose style. In total, our results reflect the integration of computational and humanistic methods to investigate a diverse range of literary questions.
Modeling the soil water retention curves of soil-gravel mixtures with regression method on the Loess Plateau of China.

PubMed

Wang, Huifang; Xiao, Bo; Wang, Mingyu; Shao, Ming'an

2013-01-01

Soil water retention parameters are critical to quantify flow and solute transport in vadose zone, while the presence of rock fragments remarkably increases their variability. Therefore a novel method for determining water retention parameters of soil-gravel mixtures is required. The procedure to generate such a model is based firstly on the determination of the quantitative relationship between the content of rock fragments and the effective saturation of soil-gravel mixtures, and then on the integration of this relationship with former analytical equations of water retention curves (WRCs). In order to find such relationships, laboratory experiments were conducted to determine WRCs of soil-gravel mixtures obtained with a clay loam soil mixed with shale clasts or pebbles in three size groups with various gravel contents. Data showed that the effective saturation of the soil-gravel mixtures with the same kind of gravels within one size group had a linear relation with gravel contents, and had a power relation with the bulk density of samples at any pressure head. Revised formulas for water retention properties of the soil-gravel mixtures are proposed to establish the water retention curved surface models of the power-linear functions and power functions. The analysis of the parameters obtained by regression and validation of the empirical models showed that they were acceptable by using either the measured data of separate gravel size group or those of all the three gravel size groups having a large size range. Furthermore, the regression parameters of the curved surfaces for the soil-gravel mixtures with a large range of gravel content could be determined from the water retention data of the soil-gravel mixtures with two representative gravel contents or bulk densities. Such revised water retention models are potentially applicable in regional or large scale field investigations of significantly heterogeneous media, where various gravel sizes and different gravel
Investing the effectiveness of retention performance in a non-volatile floating gate memory device with a core-shell structure of CdSe nanoparticles

NASA Astrophysics Data System (ADS)

Lee, Dong-Hoon; Kim, Jung-Min; Lim, Ki-Tae; Cho, Hyeong Jun; Bang, Jin Ho; Kim, Yong-Sang

2016-03-01

In this paper, we empirically investigate the retention performance of organic non-volatile floating gate memory devices with CdSe nanoparticles (NPs) as charge trapping elements. Core-structured CdSe NPs or core-shell-structured ZnS/CdSe NPs were mixed in PMMA and their performance in pentacene based device was compared. The NPs and self-organized thin tunneling PMMA inside the devices exhibited hysteresis by trapping hole during capacitance-voltage characterization. Despite of core-structured NPs showing a larger memory window, the retention time was too short to be adopted by an industry. By contrast core-shell structured NPs showed an improved retention time of >10000 seconds than core-structure NCs. Based on these results and the energy band structure, we propose the retention mechanism of each NPs. This investigation of retention performance provides a comparative and systematic study of the charging/discharging behaviors of NPs based memory devices. [Figure not available: see fulltext.
Ecological Structure Activity Relationships

EPA Science Inventory

Ecological Structure Activity Relationships, v1.00a, February 2009
ECOSAR (Ecological Structure Activity Relationships) is a personal computer software program that is used to estimate the toxicity of chemicals used in industry and discharged into water. The program predicts...
Three dimensional quantitative structure-toxicity relationship modeling and prediction of acute toxicity for organic contaminants to algae.

PubMed

Jin, Xiangqin; Jin, Minghao; Sheng, Lianxi

2014-08-01

Although numerous chemicals have been identified to have significant toxicological effect on aquatic organisms, there is still lack of a reliable, high-throughput approach to evaluate, screen and monitor the presence of organic contaminants in aquatic system. In the current study, we proposed a synthetic pipeline to automatically model and predict the acute toxicity of chemicals to algae. In the procedure, a new alignment-free three dimensional (3D) structure characterization method was described and, with this method, several 3D-quantitative structure-toxicity relationship (3D-QSTR) models were developed, from which two were found to exhibit strong internal fitting ability and high external predictive power. The best model was established by Gaussian process (GP), which was further employed to perform extrapolation on a random compound library consisting of 1014 virtually generated substituted benzenes. It was found that (i) substitution number can only exert slight influence on chemical׳s toxicity, but low-substituted benzenes seem to have higher toxicity than those of high-substituted entities, and (ii) benzenes substituted by nitro group and halogens exhibit high acute toxicity as compared to other substituents such as methyl and carboxyl groups. Subsequently, several promising candidates suggested by computational prediction were assayed by using a standard algal growth inhibition test. Consequently, four substituted benzenes, namely 2,3-dinitrophenol, 2-chloro-4-nitroaniline, 1,2,3-trinitrobenzene and 3-bromophenol, were determined to have high acute toxicity to Scenedesmus obliquus, with their EC50 values of 2.5±0.8, 10.5±2.1, 1.4±0.2 and 42.7±5.4μmol/L, respectively. Copyright © 2014 Elsevier Ltd. All rights reserved.
Pronunciation Training Facilitates the Learning and Retention of L2 Grammatical Structures

ERIC Educational Resources Information Center

Martin, Ines A.; Jackson, Carrie N.

2016-01-01

The present study investigated the impact of pronunciation training on the learning and retention of second language (L2) grammatical structures. By drawing on the phonological saliency of stress placement in German separable- and inseparable-prefix verbs, the study explored whether enhancing explicit instruction through pronunciation training can…
A review of quantitative structure-property relationships for the fate of ionizable organic chemicals in water matrices and identification of knowledge gaps.

PubMed

Nolte, Tom M; Ragas, Ad M J

2017-03-22

Many organic chemicals are ionizable by nature. After use and release into the environment, various fate processes determine their concentrations, and hence exposure to aquatic organisms. In the absence of suitable data, such fate processes can be estimated using Quantitative Structure-Property Relationships (QSPRs). In this review we compiled available QSPRs from the open literature and assessed their applicability towards ionizable organic chemicals. Using quantitative and qualitative criteria we selected the 'best' QSPRs for sorption, (a)biotic degradation, and bioconcentration. The results indicate that many suitable QSPRs exist, but some critical knowledge gaps remain. Specifically, future focus should be directed towards the development of QSPR models for biodegradation in wastewater and sediment systems, direct photolysis and reaction with singlet oxygen, as well as additional reactive intermediates. Adequate QSPRs for bioconcentration in fish exist, but more accurate assessments can be achieved using pharmacologically based toxicokinetic (PBTK) models. No adequate QSPRs exist for bioconcentration in non-fish species. Due to the high variability of chemical and biological species as well as environmental conditions in QSPR datasets, accurate predictions for specific systems and inter-dataset conversions are problematic, for which standardization is needed. For all QSPR endpoints, additional data requirements involve supplementing the current chemical space covered and accurately characterizing the test systems used.
Variability in structure of university pulmonary/critical care fellowships and retention of fellows in academic medicine.

PubMed

Nadig, Nandita R; Vanderbilt, Allison A; Ford, Dee W; Schnapp, Lynn M; Pastis, Nicholas J

2015-04-01

Individual fellowship programs are challenged to find a format of training that not only meets the Accreditation Council for Graduate Medical Education requirements, but also grooms fellows to be trusted clinicians, and encourages them to enter academic careers. This study was undertaken as part of an internal effort to evaluate and revise the program structure of the pulmonary/critical care medicine fellowship at the Medical University of South Carolina. Our objectives were to characterize variation in the training structure and specifically research opportunities of university pulmonary/critical care medicine fellowship programs, and to identify factors associated with fellow retention in academic medicine and research. A 30-item survey was developed through rigorous internal review and was administered via email. Descriptive statistics, Cronbach's alpha, correlations, Wilcoxon sign-rank test, and ANOVA were carried out. We had a response rate of 52%. Program directors reported that, within the past 5 years, 38% of their fellows remained in academic medicine and 20% remained in academics with significant research focus. We found a statistically significant association between obtaining a master's degree and remaining in academics (r = 0.559; P < 0.008). The survey also revealed statistically significant relationships between scholarly requirements (grant proposals, peer-reviewed original research projects) and the percent of fellows who graduated and remained in academics. This survey offers some insights that may be useful to fellowship program directors. In particular, advanced education in research and maximizing scholarly activities might be associated with increased academic retention among fellowship trainees.
Three-dimensional quantitative structure-activity relationship study on anti-cancer activity of 3,4-dihydroquinazoline derivatives against human lung cancer A549 cells

NASA Astrophysics Data System (ADS)

Cho, Sehyeon; Choi, Min Ji; Kim, Minju; Lee, Sunhoe; Lee, Jinsung; Lee, Seok Joon; Cho, Haelim; Lee, Kyung-Tae; Lee, Jae Yeol

2015-03-01

A series of 3,4-dihydroquinazoline derivatives with anti-cancer activities against human lung cancer A549 cells were subjected to three-dimensional quantitative structure-activity relationship (3D-QSAR) studies using the comparative molecular similarity indices analysis (CoMSIA) approaches. The most potent compound, 1 was used to align the molecules. As a result, the best prediction was obtained with CoMSIA combined the steric, electrostatic, hydrophobic, hydrogen bond donor, and hydrogen bond acceptor fields (q2 = 0.720, r2 = 0.897). This model was validated by an external test set of 6 compounds giving satisfactory predictive r2 value of 0.923 as well as the scrambling stability test. This model would guide the design of potent 3,4-dihydroquinazoline derivatives as anti-cancer agent for the treatment of human lung cancer.
Design and prediction of new anticoagulants as a selective Factor IXa inhibitor via three-dimensional quantitative structure-property relationships of amidinobenzothiophene derivatives

PubMed Central

Gao, Jia-Suo; Tong, Xu-Peng; Chang, Yi-Qun; He, Yu-Xuan; Mei, Yu-Dan; Tan, Pei-Hong; Guo, Jia-Liang; Liao, Guo-Chao; Xiao, Gao-Keng; Chen, Wei-Min; Zhou, Shu-Feng; Sun, Ping-Hua

2015-01-01

Factor IXa (FIXa), a blood coagulation factor, is specifically inhibited at the initiation stage of the coagulation cascade, promising an excellent approach for developing selective and safe anticoagulants. Eighty-four amidinobenzothiophene antithrombotic derivatives targeting FIXa were selected to establish three-dimensional quantitative structure–activity relationship (3D-QSAR) and three-dimensional quantitative structure–selectivity relationship (3D-QSSR) models using comparative molecular field analysis and comparative similarity indices analysis methods. Internal and external cross-validation techniques were investigated as well as region focusing and bootstrapping. The satisfactory q2 values of 0.753 and 0.770, and r2 values of 0.940 and 0.965 for 3D-QSAR and 3D-QSSR, respectively, indicated that the models are available to predict both the inhibitory activity and selectivity on FIXa against Factor Xa, the activated status of Factor X. This work revealed that the steric, hydrophobic, and H-bond factors should appropriately be taken into account in future rational design, especially the modifications at the 2′-position of the benzene and the 6-position of the benzothiophene in the R group, providing helpful clues to design more active and selective FIXa inhibitors for the treatment of thrombosis. On the basis of the three-dimensional quantitative structure–property relationships, 16 new potent molecules have been designed and are predicted to be more active and selective than Compound 33, which has the best activity as reported in the literature. PMID:25848211
The employee retention triad in health care: Exploring relationships amongst organisational justice, affective commitment and turnover intention.

PubMed

Perreira, Tyrone A; Berta, Whitney; Herbert, Monique

2018-04-01

To increase understanding of the relationships between organisational justice, affective commitment and turnover intention in health care. Turnover in health care is a serious concern, as it contributes to the global nursing shortage and is associated with declines in quality of care, patient safety and patient outcomes. Turnover also impacts care teams and is associated with decreased staff cohesion and morale. A survey was developed and administered to frontline nurses working in the Province of Ontario, Canada. The data were used to test a hypothetical model developed from a review of the literature. The relationships amongst the three constructs were evaluated using structural equation modelling and mediation analysis. The hypothesised model was generally supported, although we were limited to considerations of interpersonal justice, affective commitment to one's organisation and turnover intention. Interpersonal justice is associated with affective commitment to one's organisation, which is negatively associated with turnover intention. Interpersonal justice was also found to be directly and negatively associated with turnover intention. Affective commitment to one's organisation was also found to mediate the relationship between interpersonal justice and turnover intention. The examination of relationships within the "employee retention triad" in a single, comprehensive model is novel and provides new information regarding relational complexity and insights into what healthcare leaders can do to retain employees. Reducing turnover may help to decrease some of the stressors related to turnover for clinical staff remaining at the organisation such as constant onboarding and orientation of new hires, working with less experienced staff and increased workload due to decreased staffing. © 2018 John Wiley & Sons Ltd.
The effect of leverage and/or influential on structure-activity relationships.

PubMed

Bolboacă, Sorana D; Jäntschi, Lorentz

2013-05-01

In the spirit of reporting valid and reliable Quantitative Structure-Activity Relationship (QSAR) models, the aim of our research was to assess how the leverage (analysis with Hat matrix, h(i)) and the influential (analysis with Cook's distance, D(i)) of QSAR models may reflect the models reliability and their characteristics. The datasets included in this research were collected from previously published papers. Seven datasets which accomplished the imposed inclusion criteria were analyzed. Three models were obtained for each dataset (full-model, h(i)-model and D(i)-model) and several statistical validation criteria were applied to the models. In 5 out of 7 sets the correlation coefficient increased when compounds with either h(i) or D(i) higher than the threshold were removed. Withdrawn compounds varied from 2 to 4 for h(i)-models and from 1 to 13 for D(i)-models. Validation statistics showed that D(i)-models possess systematically better agreement than both full-models and h(i)-models. Removal of influential compounds from training set significantly improves the model and is recommended to be conducted in the process of quantitative structure-activity relationships developing. Cook's distance approach should be combined with hat matrix analysis in order to identify the compounds candidates for removal.
New semi-quantitative 123I-MIBG estimation method compared with scoring system in follow-up of advanced neuroblastoma: utility of total MIBG retention ratio versus scoring method.

PubMed

Sano, Yuko; Okuyama, Chio; Iehara, Tomoko; Matsushima, Shigenori; Yamada, Kei; Hosoi, Hajime; Nishimura, Tsunehiko

2012-07-01

The purpose of this study is to evaluate a new semi-quantitative estimation method using (123)I-MIBG retention ratio to assess response to chemotherapy for advanced neuroblastoma. Thirteen children with advanced neuroblastoma (International Neuroblastoma Risk Group Staging System: stage M) were examined for a total of 51 studies with (123)I-MIBG scintigraphy (before and during chemotherapy). We proposed a new semi-quantitative method using MIBG retention ratio (count obtained with delayed image/count obtained with early image with decay correction) to estimate MIBG accumulation. We analyzed total (123)I-MIBG retention ratio (TMRR: total body count obtained with delayed image/total body count obtained with early image with decay correction) and compared with a scoring method in terms of correlation with tumor markers. TMRR showed significantly higher correlations with urinary catecholamine metabolites before chemotherapy (VMA: r(2) = 0.45, P < 0.05, HVA: r(2) = 0.627, P < 0.01) than MIBG score (VMA: r(2) = 0.19, P = 0.082, HVA: r(2) = 0.25, P = 0.137). There were relatively good correlations between serial change of TMRR and those of urinary catecholamine metabolites (VMA: r(2) = 0.274, P < 0.001, HVA: r(2) = 0.448, P < 0.0001) compared with serial change of MIBG score and those of tumor markers (VMA: r(2) = 0.01, P = 0.537, HVA: 0.084, P = 0.697) during chemotherapy for advanced neuroblastoma. TMRR could be a useful semi-quantitative method for estimating early response to chemotherapy of advanced neuroblastoma because of its high correlation with urine catecholamine metabolites.
Coupled Analysis of In Vitro and Histology Tissue Samples to Quantify Structure-Function Relationship

PubMed Central

Acar, Evrim; Plopper, George E.; Yener, Bülent

2012-01-01

The structure/function relationship is fundamental to our understanding of biological systems at all levels, and drives most, if not all, techniques for detecting, diagnosing, and treating disease. However, at the tissue level of biological complexity we encounter a gap in the structure/function relationship: having accumulated an extraordinary amount of detailed information about biological tissues at the cellular and subcellular level, we cannot assemble it in a way that explains the correspondingly complex biological functions these structures perform. To help close this information gap we define here several quantitative temperospatial features that link tissue structure to its corresponding biological function. Both histological images of human tissue samples and fluorescence images of three-dimensional cultures of human cells are used to compare the accuracy of in vitro culture models with their corresponding human tissues. To the best of our knowledge, there is no prior work on a quantitative comparison of histology and in vitro samples. Features are calculated from graph theoretical representations of tissue structures and the data are analyzed in the form of matrices and higher-order tensors using matrix and tensor factorization methods, with a goal of differentiating between cancerous and healthy states of brain, breast, and bone tissues. We also show that our techniques can differentiate between the structural organization of native tissues and their corresponding in vitro engineered cell culture models. PMID:22479315
Critical evaluation of a simple retention time predictor based on LogKow as a complementary tool in the identification of emerging contaminants in water.

PubMed

Bade, Richard; Bijlsma, Lubertus; Sancho, Juan V; Hernández, Felix

2015-07-01

There has been great interest in environmental analytical chemistry in developing screening methods based on liquid chromatography-high resolution mass spectrometry (LC-HRMS) for emerging contaminants. Using HRMS, compound identification relies on the high mass resolving power and mass accuracy attainable by these analyzers. When dealing with wide-scope screening, retention time prediction can be a complementary tool for the identification of compounds, and can also reduce tedious data processing when several peaks appear in the extracted ion chromatograms. There are many in silico, Quantitative Structure-Retention Relationship methods available for the prediction of retention time for LC. However, most of these methods use commercial software to predict retention time based on various molecular descriptors. This paper explores the applicability and makes a critical discussion on a far simpler and cheaper approach to predict retention times by using LogKow. The predictor was based on a database of 595 compounds, their respective LogKow values and a chromatographic run time of 18min. Approximately 95% of the compounds were found within 4.0min of their actual retention times, and 70% within 2.0min. A predictor based purely on pesticides was also made, enabling 80% of these compounds to be found within 2.0min of their actual retention times. To demonstrate the utility of the predictors, they were successfully used as an additional tool in the identification of 30 commonly found emerging contaminants in water. Furthermore, a comparison was made by using different mass extraction windows to minimize the number of false positives obtained. Copyright © 2015 Elsevier B.V. All rights reserved.
Teacher Decision-Making in Student Retention.

ERIC Educational Resources Information Center

Cross, Ray

This investigation at a southern Texas school district examined three factors that bear on teachers' decisions to recommend first- and second-grade students for retention: (1) criteria used by teachers, (2) degree to which criteria are common among teachers, and (3) relationship of recommendations for promotion or retention to objective measures…

A statistical learning approach to the modeling of chromatographic retention of oligonucleotides incorporating sequence and secondary structure data

PubMed Central

Sturm, Marc; Quinten, Sascha; Huber, Christian G.; Kohlbacher, Oliver

2007-01-01

We propose a new model for predicting the retention time of oligonucleotides. The model is based on ν support vector regression using features derived from base sequence and predicted secondary structure of oligonucleotides. Because of the secondary structure information, the model is applicable even at relatively low temperatures where the secondary structure is not suppressed by thermal denaturing. This makes the prediction of oligonucleotide retention time for arbitrary temperatures possible, provided that the target temperature lies within the temperature range of the training data. We describe different possibilities of feature calculation from base sequence and secondary structure, present the results and compare our model to existing models. PMID:17567619
Design, synthesis, antiviral bioactivity and three-dimensional quantitative structure-activity relationship study of novel ferulic acid ester derivatives containing quinazoline moiety.

PubMed

Wu, Zengxue; Zhang, Jian; Chen, Jixiang; Pan, Jianke; Zhao, Lei; Liu, Dengyue; Zhang, Awei; Chen, Jin; Hu, Deyu; Song, Baoan

2017-10-01

Ferulic acid and quinazoline derivatives possess good antiviral activities. In order to develop novel compounds with high antiviral activities, a series of ferulic acid ester derivatives containing quinazoline were synthesized and evaluated for their antiviral activities. Bioassays indicated that some of the compounds exhibited good antiviral activities in vivo against tobacco mosaic virus (TMV) and cucumber mosaic virus (CMV). One of the compounds demonstrated significant curative and protective activities against TMV and CMV, with EC 50 values of 162.14, 114.61 and 255.49, 138.81 mg L -1 , respectively, better than those of ningnanmycin (324.51, 168.84 and 373.88, 272.70 mg L -1 ). The values of q 2 and r 2 for comparative molecular field analysis and comparative molecular similarity index analysis in the TMV (0.508, 0.663 and 0.992, 0.930) and CMV (0.530, 0.626 and 0.997, 0.981) models presented good predictive abilities. Some of the title compounds demonstrated good antiviral activities. Three-dimensional quantitative structure-activity relationship models revealed that the antiviral activities depend on steric and electrostatic properties. These results could provide significant structural insights for the design of highly active ferulic acid derivatives. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.
Notes on quantitative structure-properties relationships (QSPR) (1): A discussion on a QSPR dimensionality paradox (QSPR DP) and its quantum resolution.

PubMed

Carbó-Dorca, Ramon; Gallegos, Ana; Sánchez, Angel J

2009-05-01

Classical quantitative structure-properties relationship (QSPR) statistical techniques unavoidably present an inherent paradoxical computational context. They rely on the definition of a Gram matrix in descriptor spaces, which is used afterwards to reduce the original dimension via several possible kinds of algebraic manipulations. From there, effective models for the computation of unknown properties of known molecular structures are obtained. However, the reduced descriptor dimension causes linear dependence within the set of discrete vector molecular representations, leading to positive semi-definite Gram matrices in molecular spaces. To resolve this QSPR dimensionality paradox (QSPR DP) here is proposed to adopt as starting point the quantum QSPR (QQSPR) computational framework perspective, where density functions act as infinite dimensional descriptors. The fundamental QQSPR equation, deduced from employing quantum expectation value numerical evaluation, can be approximately solved in order to obtain models exempt of the QSPR DP. The substitution of the quantum similarity matrix by an empirical Gram matrix in molecular spaces, build up with the original non manipulated discrete molecular descriptor vectors, permits to obtain classical QSPR models with the same characteristics as in QQSPR, that is: possessing a certain degree of causality and explicitly independent of the descriptor dimension. 2008 Wiley Periodicals, Inc.
Molecular modeling of polymers 16. Gaseous diffusion in polymers: a quantitative structure-property relationship (QSPR) analysis.

PubMed

Patel, H C; Tokarski, J S; Hopfinger, A J

1997-10-01

The purpose of this study was to identify the key physicochemical molecular properties of polymeric materials responsible for gaseous diffusion in the polymers. Quantitative structure-property relationships, QSPRs were constructed using a genetic algorithm on a training set of 16 polymers for which CO2, N2, O2 diffusion constants were measured. Nine physicochemical properties of each of the polymers were used in the trial basis set for QSPR model construction. The linear cross-correlation matrices were constructed and investigated for colinearity among the members of the training sets. Common water diffusion measures for a limited training set of six polymers was used to construct a "semi-QSPR" model. The bulk modulus of the polymer was overwhelmingly found to be the dominant physicochemical polymer property that governs CO2, N2 and O2 diffusion. Some secondary physicochemical properties controlling diffusion, including conformational entropy, were also identified as correlation descriptors. Very significant QSPR diffusion models were constructed for all three gases. Cohesive energy was identified as the main correlation physicochemical property with aqueous diffusion measures. The dominant role of polymer bulk modulus on gaseous diffusion makes it difficult to develop criteria for selective transport of gases through polymers. Moreover, high bulk moduli are predicted to be necessary for effective gas barrier materials. This property requirement may limit the processing and packaging features of the material. Aqueous diffusion in polymers may occur by a different mechanism than gaseous diffusion since bulk modulus does not correlate with aqueous diffusion, but rather cohesive energy of the polymer.
Rational Quantitative Structure-Activity Relationship (RQSAR) Screen for PXR and CAR Isoform-Specific Nuclear Receptor Ligands

PubMed Central

Dring, Ann M.; Anderson, Linnea E.; Qamar, Saima; Stoner, Matthew A.

2010-01-01

Constitutive androstane receptor (CAR) and pregnane X receptor (PXR) are closely related orphan nuclear receptor proteins that share several ligands and target overlapping sets of genes involved in homeostasis and all phases of drug metabolism. CAR and PXR are involved in the development of certain diseases, including diabetes, metabolic syndrome and obesity. Ligand screens for these receptors so far have typically focused on steroid hormone analogs with pharmacophore-based approaches, only to find relatively few new hits. Multiple CAR isoforms have been detected in human liver, with the most abundant being the constitutively active reference, CAR1, and the ligand-dependent isoform CAR3. It has been assumed that any compound that binds CAR1 should also activate CAR3, and so CAR3 can be used as a ligand-activated surrogate for CAR1 studies. The possibility of CAR3-specific ligands has not, so far, been addressed. To investigate the differences between CAR1, CAR3 and PXR, and to look for more CAR ligands that may be of use in quantitative structure-activity relationship (QSAR) studies, we performed a luciferase transactivation assay screen of 60 mostly non-steroid compounds. Known active compounds with different core chemistries were chosen as starting points and structural variants were rationally selected for screening. Distinct differences in agonist versus inverse agonist/antagonist effects were seen in 49 compounds that had some ligand effect on at least one receptor and 18 that had effects on all three receptors; eight were CAR1 ligands only, three were CAR3 only ligands and four affected PXR only. This work provides evidence for new CAR ligands, some of which have CAR3-specific effects, and provides observational data on CAR and PXR ligands with which to inform in silico strategies. Compounds that demonstrated unique activity on any one receptor are potentially valuable diagnostic tools for the investigation of in vivo molecular targets. PMID:20869355
Relationships of flour solvent retention capacity, secondary structure and rheological properties with the cookie making characteristics of wheat cultivars.

PubMed

Kaur, Amritpal; Singh, Narpinder; Kaur, Seeratpreet; Ahlawat, Arvind Kumar; Singh, Anju Mahendru

2014-09-01

The relationships of grain, flour solvent retention capacity (SRC) and dough rheological properties with the cookie making properties of wheat cultivars were evaluated. Cultivars with higher proportion of intermolecular-β-sheets+antiparallel β sheets and lower α-helix had greater gluten strength. The grain weight and diameter positively correlated with the proportion of fine particles and the cookie spread factor (SF) and negatively to the grain hardness (GH) and Na2CO3 SRC. The SF was higher in the flour with a higher amount of fine particle and with a lower Na2CO3 SRC and dough stability (DS). The breaking strength (BS) of cookies was positively correlated to lactic acid (LA) SRC, DS, peak time, sedimentation value (SV), G' and G″. Na2CO3 SRC and GH were strongly correlated. The gluten performance index showed a strong positive correlation with SV, DS, G' and G″. The water absorption had a significant positive correlation with sucrose SRC and LASRC. Cultivars with higher GH produced higher amount of coarse particles in flours that had higher Na2CO3 SRC and lower cookie SF. Copyright © 2014 Elsevier Ltd. All rights reserved.
Effects of Cooperative, Competitive, and Individualistic Learning Structures on College Student Achievement and Peer Relationships: A Series of Meta-Analyses

ERIC Educational Resources Information Center

Hilk, Caroline Lual

2013-01-01

This series of meta-analyses investigates the effects of social interdependence (cooperative, competitive, and individualistic learning structures) on achievement and peer relationships among college students. This study quantitatively synthesized the literature on the effects of social interdependence on achievement and peer relationship outcomes…
An Exploratory Study to Assess Individual and Structural Level Barriers Associated With Poor Retention and Re-engagement in Care Among Persons Living With HIV/AIDS.

PubMed

Colasanti, Jonathan; Stahl, Natalie; Farber, Eugene W; Del Rio, Carlos; Armstrong, Wendy S

2017-02-01

Retention in care is the most challenging step along the HIV care continuum. Many patients who engage in care and achieve viral suppression have care interruptions, characterized by moving in and out of care ("churn"). Poor retention has clinical consequences and contributes to new HIV transmissions, but how to predict or prevent it remains elusive. This study sought to understand the relationship between individual- and structural-level barriers, and poor retention for persons living with HIV/AIDS in Atlanta, GA. We administered a survey, through interviews, with HIV-infected patients continuously retained in care for 6 years ("continuously retained," n = 32) and patients with recent gaps in care ("unretained" n = 27). We assessed individual-level protective factors for successful engagement (self-efficacy, resilience, perceived social support, and disclosure), risk factors for poor engagement (substance use, mental illness, and stigma), and structural/systemic-level barriers (financial and housing instability, transportation, food insecurity, communication barriers, and incarceration history). Chi-square and Mann-Whitney U tests were used to compare the 2 populations. Both continuously retained and unretained populations had high rates of prior viral suppression but few unretained patients were virologically suppressed upon return to care (11%). Younger age, crack cocaine use, food insecurity, financial instability, housing instability, and phone number changes in the past year were significantly more likely to be present in the unretained population. Our findings suggest the need for targeted risk assessment tools to predict the highest-risk patients for poor retention whereby public health interventions can be directed to those individuals.
Quantitative structure-activity relationships (QSARs) for the transformation of organic micropollutants during oxidative water treatment.

PubMed

Lee, Yunho; von Gunten, Urs

2012-12-01

Various oxidants such as chlorine, chlorine dioxide, ferrate(VI), ozone, and hydroxyl radicals can be applied for eliminating organic micropollutant by oxidative transformation during water treatment in systems such as drinking water, wastewater, and water reuse. Over the last decades, many second-order rate constants (k) have been determined for the reaction of these oxidants with model compounds and micropollutants. Good correlations (quantitative structure-activity relationships or QSARs) are often found between the k-values for an oxidation reaction of closely related compounds (i.e. having a common organic functional group) and substituent descriptor variables such as Hammett or Taft sigma constants. In this study, we developed QSARs for the oxidation of organic and some inorganic compounds and organic micropollutants transformation during oxidative water treatment. A number of 18 QSARs were developed based on overall 412 k-values for the reaction of chlorine, chlorine dioxide, ferrate, and ozone with organic compounds containing electron-rich moieties such as phenols, anilines, olefins, and amines. On average, 303 out of 412 (74%) k-values were predicted by these QSARs within a factor of 1/3-3 compared to the measured values. For HO(·) reactions, some principles and estimation methods of k-values (e.g. the Group Contribution Method) are discussed. The developed QSARs and the Group Contribution Method could be used to predict the k-values for various emerging organic micropollutants. As a demonstration, 39 out of 45 (87%) predicted k-values were found within a factor 1/3-3 compared to the measured values for the selected emerging micropollutants. Finally, it is discussed how the uncertainty in the predicted k-values using the QSARs affects the accuracy of prediction for micropollutant elimination during oxidative water treatment. Copyright © 2012 Elsevier Ltd. All rights reserved.
Estimating the Potential Toxicity of Chemicals Associated with Hydraulic Fracturing Operations Using Quantitative Structure-Activity Relationship Modeling.

PubMed

Yost, Erin E; Stanek, John; DeWoskin, Robert S; Burgoon, Lyle D

2016-07-19

The United States Environmental Protection Agency (EPA) identified 1173 chemicals associated with hydraulic fracturing fluids, flowback, or produced water, of which 1026 (87%) lack chronic oral toxicity values for human health assessments. To facilitate the ranking and prioritization of chemicals that lack toxicity values, it may be useful to employ toxicity estimates from quantitative structure-activity relationship (QSAR) models. Here we describe an approach for applying the results of a QSAR model from the TOPKAT program suite, which provides estimates of the rat chronic oral lowest-observed-adverse-effect level (LOAEL). Of the 1173 chemicals, TOPKAT was able to generate LOAEL estimates for 515 (44%). To address the uncertainty associated with these estimates, we assigned qualitative confidence scores (high, medium, or low) to each TOPKAT LOAEL estimate, and found 481 to be high-confidence. For 48 chemicals that had both a high-confidence TOPKAT LOAEL estimate and a chronic oral reference dose from EPA's Integrated Risk Information System (IRIS) database, Spearman rank correlation identified 68% agreement between the two values (permutation p-value =1 × 10(-11)). These results provide support for the use of TOPKAT LOAEL estimates in identifying and prioritizing potentially hazardous chemicals. High-confidence TOPKAT LOAEL estimates were available for 389 of 1026 hydraulic fracturing-related chemicals that lack chronic oral RfVs and OSFs from EPA-identified sources, including a subset of chemicals that are frequently used in hydraulic fracturing fluids.
Quantitative theory of hydrophobic effect as a driving force of protein structure

PubMed Central

Perunov, Nikolay; England, Jeremy L

2014-01-01

Various studies suggest that the hydrophobic effect plays a major role in driving the folding of proteins. In the past, however, it has been challenging to translate this understanding into a predictive, quantitative theory of how the full pattern of sequence hydrophobicity in a protein shapes functionally important features of its tertiary structure. Here, we extend and apply such a phenomenological theory of the sequence-structure relationship in globular protein domains, which had previously been applied to the study of allosteric motion. In an effort to optimize parameters for the model, we first analyze the patterns of backbone burial found in single-domain crystal structures, and discover that classic hydrophobicity scales derived from bulk physicochemical properties of amino acids are already nearly optimal for prediction of burial using the model. Subsequently, we apply the model to studying structural fluctuations in proteins and establish a means of identifying ligand-binding and protein–protein interaction sites using this approach. PMID:24408023
Three-dimensional quantitative structure-property relationship (3D-QSPR) models for prediction of thermodynamic properties of polychlorinated biphenyls (PCBs): enthalpy of vaporization.

PubMed

Puri, Swati; Chickos, James S; Welsh, William J

2002-01-01

Three-dimensional Quantitative Structure-Property Relationship (QSPR) models have been derived using Comparative Molecular Field Analysis (CoMFA) to correlate the vaporization enthalpies of a representative set of polychlorinated biphenyls (PCBs) at 298.15 K with their CoMFA-calculated physicochemical properties. Various alignment schemes, such as inertial, as is, and atom fit, were employed in this study. The CoMFA models were also developed using different partial charge formalisms, namely, electrostatic potential (ESP) charges and Gasteiger-Marsili (GM) charges. The most predictive model for vaporization enthalpy (Delta(vap)H(m)(298.15 K)), with atom fit alignment and Gasteiger-Marsili charges, yielded r2 values 0.852 (cross-validated) and 0.996 (conventional). The vaporization enthalpies of PCBs increased with the number of chlorine atoms and were found to be larger for the meta- and para-substituted isomers. This model was used to predict Delta(vap)H(m)(298.15 K) of the entire set of 209 PCB congeners.
Modeling the Soil Water Retention Curves of Soil-Gravel Mixtures with Regression Method on the Loess Plateau of China

PubMed Central

Wang, Huifang; Xiao, Bo; Wang, Mingyu; Shao, Ming'an

2013-01-01

Soil water retention parameters are critical to quantify flow and solute transport in vadose zone, while the presence of rock fragments remarkably increases their variability. Therefore a novel method for determining water retention parameters of soil-gravel mixtures is required. The procedure to generate such a model is based firstly on the determination of the quantitative relationship between the content of rock fragments and the effective saturation of soil-gravel mixtures, and then on the integration of this relationship with former analytical equations of water retention curves (WRCs). In order to find such relationships, laboratory experiments were conducted to determine WRCs of soil-gravel mixtures obtained with a clay loam soil mixed with shale clasts or pebbles in three size groups with various gravel contents. Data showed that the effective saturation of the soil-gravel mixtures with the same kind of gravels within one size group had a linear relation with gravel contents, and had a power relation with the bulk density of samples at any pressure head. Revised formulas for water retention properties of the soil-gravel mixtures are proposed to establish the water retention curved surface models of the power-linear functions and power functions. The analysis of the parameters obtained by regression and validation of the empirical models showed that they were acceptable by using either the measured data of separate gravel size group or those of all the three gravel size groups having a large size range. Furthermore, the regression parameters of the curved surfaces for the soil-gravel mixtures with a large range of gravel content could be determined from the water retention data of the soil-gravel mixtures with two representative gravel contents or bulk densities. Such revised water retention models are potentially applicable in regional or large scale field investigations of significantly heterogeneous media, where various gravel sizes and different gravel
A dynamic processes study of PM retention by trees under different wind conditions.

PubMed

Xie, Changkun; Kan, Liyan; Guo, Jiankang; Jin, Sijia; Li, Zhigang; Chen, Dan; Li, Xin; Che, Shengquan

2018-02-01

Particulate matter (PM) is one of the most serious environmental problems, exacerbating respiratory and vascular illnesses. Plants have the ability to reduce non-point source PM pollution through retention on leaves and branches. Studies of the dynamic processes of PM retention by plants and the mechanisms influencing this process will help to improve the efficiency of urban greening for PM reduction. We examined dynamic processes of PM retention and the major factors influencing PM retention by six trees with different branch structure characteristics in wind tunnel experiments at three different wind speeds. The results showed that the changes of PM numbers retained by plant leaves over time were complex dynamic processes for which maximum values could exceed minimum values by over 10 times. The average value of PM measured in multiple periods and situations can be considered a reliable indicator of the ability of the plant to retain PM. The dynamic processes were similar for PM 10 and PM 2.5 . They could be clustered into three groups simulated by continually-rising, inverse U-shaped, and U-shaped polynomial functions, respectively. The processes were the synthetic effect of characteristics such as species, wind speed, period of exposure and their interactions. Continually-rising functions always explained PM retention in species with extremely complex branch structure. Inverse U-shaped processes explained PM retention in species with relatively simple branch structure and gentle wind. The U-shaped processes mainly explained PM retention at high wind speeds and in species with a relatively simple crown. These results indicate that using plants with complex crowns in urban greening and decreasing wind speed in plant communities increases the chance of continually-rising or inverse U-shaped relationships, which have a positive effect in reducing PM pollution. Copyright © 2017 Elsevier Ltd. All rights reserved.
Synthesis and quantitative structure-activity relationship (QSAR) study of novel isoxazoline and oxime derivatives of podophyllotoxin as insecticidal agents.

PubMed

Wang, Yi; Shao, Yonghua; Wang, Yangyang; Fan, Lingling; Yu, Xiang; Zhi, Xiaoyan; Yang, Chun; Qu, Huan; Yao, Xiaojun; Xu, Hui

2012-08-29

In continuation of our program aimed at the discovery and development of natural-product-based insecticidal agents, 33 isoxazoline and oxime derivatives of podophyllotoxin modified in the C and D rings were synthesized and their structures were characterized by Proton nuclear magnetic resonance ((1)H NMR), high-resolution mass spectrometry (HRMS), electrospray ionization-mass spectrometry (ESI-MS), optical rotation, melting point (mp), and infrared (IR) spectroscopy. The stereochemical configurations of compounds 5e, 5f, and 9f were unambiguously determined by X-ray crystallography. Their insecticidal activity was evaluated against the pre-third-instar larvae of northern armyworm, Mythimna separata (Walker), in vivo. Compounds 5e, 9c, 11g, and 11h especially exhibited more promising insecticidal activity than toosendanin, a commercial botanical insecticide extracted from Melia azedarach . A genetic algorithm combined with multiple linear regression (GA-MLR) calculation is performed by the MOBY DIGS package. Five selected descriptors are as follows: one two-dimensional (2D) autocorrelation descriptor (GATS4e), one edge adjacency indice (EEig06x), one RDF descriptor (RDF080v), one three-dimensional (3D) MoRSE descriptor (Mor09v), and one atom-centered fragment (H-052) descriptor. Quantitative structure-activity relationship studies demonstrated that the insecticidal activity of these compounds was mainly influenced by many factors, such as electronic distribution, steric factors, etc. For this model, the standard deviation error in prediction (SDEP) is 0.0592, the correlation coefficient (R(2)) is 0.861, and the leave-one-out cross-validation correlation coefficient (Q(2)loo) is 0.797.
Prediction of anticancer property of bowsellic acid derivatives by quantitative structure activity relationship analysis and molecular docking study.

PubMed

Satpathy, Raghunath; Guru, R K; Behera, R; Nayak, B

2015-01-01

Boswellic acid consists of a series of pentacyclic triterpene molecules that are produced by the plant Boswellia serrata. The potential applications of Bowsellic acid for treatment of cancer have been focused here. To predict the property of the bowsellic acid derivatives as anticancer compounds by various computational approaches. In this work, all total 65 derivatives of bowsellic acids from the PubChem database were considered for the study. After energy minimization of the ligands various types of molecular descriptors were computed and corresponding two-dimensional quantitative structure activity relationship (QSAR) models were obtained by taking Andrews coefficient as the dependent variable. Different types of comparative analysis were used for QSAR study are multiple linear regression, partial least squares, support vector machines and artificial neural network. From the study geometrical descriptors shows the highest correlation coefficient, which indicates the binding factor of the compound. To evaluate the anticancer property molecular docking study of six selected ligands based on Andrews affinity were performed with nuclear factor-kappa protein kinase (Protein Data Bank ID 4G3D), which is an established therapeutic target for cancers. Along with QSAR study and docking result, it was predicted that bowsellic acid can also be treated as a potential anticancer compound. Along with QSAR study and docking result, it was predicted that bowsellic acid can also be treated as a potential anticancer compound.
CULTURAL COMPETENCE IN OUTPATIENT SUBSTANCE ABUSE TREATMENT: MEASUREMENT AND RELATIONSHIP TO WAIT TIME AND RETENTION

PubMed Central

Guerrero, Erick; Andrews, Christina M.

2011-01-01

BACKGROUND Culturally competent practice is broadly acknowledged to be an important strategy to increase the quality of services for racial/ethnic minorities in substance abuse treatment. However, few empirically derived measures of organizational cultural competence exist, and relatively little is known about how these measures affect treatment outcomes. METHOD Using a nationally representative sample of outpatient substance abuse treatment (OSAT) programs, this study used item response theory to create two measures of cultural competence-organizational practices and managers' culturally sensitive beliefs—and examined their relationship to client wait time and retention using Poisson regression modeling RESULTS The most common and precisely measured organizational practices reported by OSAT managers included matching providers and clients based on language/dialect; offering cross-cultural training; and fostering connections with community and faith-based organizations connected to racial and ethnic minority groups. The most culturally sensitive belief among OSAT managers was support for language/dialect matching for racial and ethnic minority clients. Results of regression modeling indicate that organizational practices were not related to either outcome. However, managers' culturally sensitive beliefs were negatively associated with average wait time (p < 0.05), and positively associated with average retention (p < 0.01). CONCLUSIONS Managers' culturally sensitive beliefs—considered to be influential for effective implementation of culturally competent practices—may be particularly relevant in influencing wait time and retention in OSAT organizations that treat Latinos and African American clients. PMID:21680111
Quantitative structure--property relationships for enhancing predictions of synthetic organic chemical removal from drinking water by granular activated carbon.

PubMed

Magnuson, Matthew L; Speth, Thomas F

2005-10-01

Granular activated carbon is a frequently explored technology for removing synthetic organic contaminants from drinking water sources. The success of this technology relies on a number of factors based not only on the adsorptive properties of the contaminant but also on properties of the water itself, notably the presence of substances in the water which compete for adsorption sites. Because it is impractical to perform field-scale evaluations for all possible contaminants, the pore surface diffusion model (PSDM) has been developed and used to predict activated carbon column performance using single-solute isotherm data as inputs. Many assumptions are built into this model to account for kinetics of adsorption and competition for adsorption sites. This work further evaluates and expands this model, through the use of quantitative structure-property relationships (QSPRs) to predict the effect of natural organic matter fouling on activated carbon adsorption of specific contaminants. The QSPRs developed are based on a combination of calculated topographical indices and quantum chemical parameters. The QSPRs were evaluated in terms of their statistical predictive ability,the physical significance of the descriptors, and by comparison with field data. The QSPR-enhanced PSDM was judged to give results better than what could previously be obtained.
Biochemical interpretation of quantitative structure-activity relationships (QSAR) for biodegradation of N-heterocycles: a complementary approach to predict biodegradability.

PubMed

Philipp, Bodo; Hoff, Malte; Germa, Florence; Schink, Bernhard; Beimborn, Dieter; Mersch-Sundermann, Volker

2007-02-15

Prediction of the biodegradability of organic compounds is an ecologically desirable and economically feasible tool for estimating the environmental fate of chemicals. We combined quantitative structure-activity relationships (QSAR) with the systematic collection of biochemical knowledge to establish rules for the prediction of aerobic biodegradation of N-heterocycles. Validated biodegradation data of 194 N-heterocyclic compounds were analyzed using the MULTICASE-method which delivered two QSAR models based on 17 activating (OSAR 1) and on 16 inactivating molecular fragments (GSAR 2), which were statistically significantly linked to efficient or poor biodegradability, respectively. The percentages of correct classifications were over 99% for both models, and cross-validation resulted in 67.9% (GSAR 1) and 70.4% (OSAR 2) correct predictions. Biochemical interpretation of the activating and inactivating characteristics of the molecular fragments delivered plausible mechanistic interpretations and enabled us to establish the following biodegradation rules: (1) Target sites for amidohydrolases and for cytochrome P450 monooxygenases enhance biodegradation of nonaromatic N-heterocycles. (2) Target sites for molybdenum hydroxylases enhance biodegradation of aromatic N-heterocycles. (3) Target sites for hydratation by an urocanase-like mechanism enhance biodegradation of imidazoles. Our complementary approach represents a feasible strategy for generating concrete rules for the prediction of biodegradability of organic compounds.
A Quantitative Structure Activity Relationship for acute oral toxicity of pesticides on rats: Validation, domain of application and prediction.

PubMed

Hamadache, Mabrouk; Benkortbi, Othmane; Hanini, Salah; Amrane, Abdeltif; Khaouane, Latifa; Si Moussa, Cherif

2016-02-13

Quantitative Structure Activity Relationship (QSAR) models are expected to play an important role in the risk assessment of chemicals on humans and the environment. In this study, we developed a validated QSAR model to predict acute oral toxicity of 329 pesticides to rats because a few QSAR models have been devoted to predict the Lethal Dose 50 (LD50) of pesticides on rats. This QSAR model is based on 17 molecular descriptors, and is robust, externally predictive and characterized by a good applicability domain. The best results were obtained with a 17/9/1 Artificial Neural Network model trained with the Quasi Newton back propagation (BFGS) algorithm. The prediction accuracy for the external validation set was estimated by the Q(2)ext and the root mean square error (RMS) which are equal to 0.948 and 0.201, respectively. 98.6% of external validation set is correctly predicted and the present model proved to be superior to models previously published. Accordingly, the model developed in this study provides excellent predictions and can be used to predict the acute oral toxicity of pesticides, particularly for those that have not been tested as well as new pesticides. Copyright © 2015 Elsevier B.V. All rights reserved.

The relationship between dermal papillary structure and skin surface properties, color, and elasticity.

PubMed

Mizukoshi, K; Nakamura, T; Oba, A

2016-08-01

The skin contains an undulating structure called the dermal papillary structure between the border of the epidermis and dermis. The physiological importance of the dermal papillary structures has been discussed, however, the dermal papillary structures have never been evaluated for their contribution to skin appearance. In this study, we investigated the correlation between the dermal papillary structure and skin color and elasticity. In addition, the relationship was validated with skin model experiments. The dermal papillary structures in the skin of the female cheek were quantitatively measured by in vivo confocal laser scanning microscopy images. In addition, the skin color and elasticity were measured at the same site. A skin model with dermal papilla-like structures was created by referring to the optical and shape properties of the skin using agar gel and a scattering sheet. Correlations were found between the dermal papillary structures and skin color irregularity and skin elasticity. These relationships were verified by the experiments employing a skin model. The results of this study indicated that the dermal papillary structure is also an important factor for skin appearance such as color and elasticity. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
Measuring faculty retention and success in academic medicine.

PubMed

Ries, Andrew; Wingard, Deborah; Gamst, Anthony; Larsen, Catherine; Farrell, Elizabeth; Reznik, Vivian

2012-08-01

To develop and demonstrate the usefulness of quantitative methods for assessing retention and academic success of junior faculty in academic medicine. The authors created matched sets of participants and nonparticipants in a junior faculty development program based on hire date and academic series for newly hired assistant professors at the University of California, San Diego (UCSD), School of Medicine between 1988 and 2005. They used Kaplan-Meier and Cox proportional hazards survival analyses to characterize the influence of covariates, including gender, ethnicity, and program participation, on retention. They also developed a new method for quantifying academic success based on several measures including (1) leadership and professional activities, (2) honors and awards, (3) research grants, (4) teaching and mentoring/advising activities, and (5) publications. The authors then used these measures to compare matched pairs of participating and nonparticipating faculty who were subsequently promoted and remained at UCSD. Compared with matched nonparticipants, the retention of junior faculty who participated in the faculty development program was significantly higher. Among those who were promoted and remained at UCSD, the academic success of faculty development participants was consistently greater than that of matched nonparticipants. This difference reached statistical significance for leadership and professional activities. Using better quantitative methods for evaluating retention and academic success will improve understanding and research in these areas. In this study, use of such methods indicated that organized junior faculty development programs have positive effects on faculty retention and may facilitate success in academic medicine.
The relationship between quantitative measures of disc height and disc signal intensity with Pfirrmann score of disc degeneration.

PubMed

Salamat, Sara; Hutchings, John; Kwong, Clemens; Magnussen, John; Hancock, Mark J

2016-01-01

To assess the relationship between quantitative measures of disc height and signal intensity with the Pfirrmann disc degeneration scoring system and to test the inter-rater reliability of the quantitative measures. Participants were 76 people who had recently recovered from their last episode of acute low back pain and underwent MRI scan on a single 3T machine. At all 380 lumbar discs, quantitative measures of disc height and signal intensity were made by 2 independent raters and compared to Pfirrmann scores from a single radiologist. For quantitative measures of disc height and signal intensity a "raw" score and 2 adjusted ratios were calculated and the relationship with Pfirrmann scores was assessed. The inter-tester reliability of quantitative measures was also investigated. There was a strong linear relationship between quantitative disc signal intensity and Pfirrmann scores for grades 1-4, but not for grades 4 and 5. For disc height only, Pfirrmann grade 5 had significantly reduced disc height compared to all other grades. Results were similar regardless of whether raw or adjusted scores were used. Inter-rater reliability for the quantitative measures was excellent (ICC > 0.97). Quantitative measures of disc signal intensity were strongly related to Pfirrmann scores from grade 1 to 4; however disc height only differentiated between grade 4 and 5 Pfirrmann scores. Using adjusted ratios for quantitative measures of disc height or signal intensity did not significantly alter the relationship with Pfirrmann scores.
QSAR for cholinesterase inhibition by organophosphorus esters and CNDO/2 calculations for organophosphorus ester hydrolysis. [quantitative structure-activity relationship, complete neglect of differential overlap

NASA Technical Reports Server (NTRS)

Johnson, H.; Kenley, R. A.; Rynard, C.; Golub, M. A.

1985-01-01

Quantitative structure-activity relationships were derived for acetyl- and butyrylcholinesterase inhibition by various organophosphorus esters. Bimolecular inhibition rate constants correlate well with hydrophobic substituent constants, and with the presence or absence of cationic groups on the inhibitor, but not with steric substituent constants. CNDO/2 calculations were performed on a separate set of organophosphorus esters, RR-primeP(O)X, where R and R-prime are alkyl and/or alkoxy groups and X is fluorine, chlorine or a phenoxy group. For each subset with the same X, the CNDO-derived net atomic charge at the central phosphorus atom in the ester correlates well with the alkaline hydrolysis rate constant. For the whole set of esters with different X, two equations were derived that relate either charge and leaving group steric bulk, or orbital energy and bond order to the hydrolysis rate constant.
Misconceived Relationships between Logical Positivism and Quantitative Research: An Analysis in the Framework of Ian Hacking.

ERIC Educational Resources Information Center

Yu, Chong Ho

Although quantitative research methodology is widely applied by psychological researchers, there is a common misconception that quantitative research is based on logical positivism. This paper examines the relationship between quantitative research and eight major notions of logical positivism: (1) verification; (2) pro-observation; (3)…
Good mates retain us right: investigating the relationship between mate retention strategies, mate value, and relationship satisfaction.

PubMed

Salkicevic, Svjetlana; Stanic, Ajana L; Grabovac, Masa T

2014-12-07

Mate retention strategies are an important tool in keeping a partner, and their use is determined by the mate value (MV) of the partner one is trying to keep. The type of strategy used is also dependent on one's own MV: mates of lower MV are more prone to exhibiting strategies that are cost-inflicting for their partners, whereas partner-benefiting strategies are used by mates of higher value. The type of strategies used affects relationship satisfaction (RS), and is also affected by the perceived difference in MVs. However, it is unclear how someone's perception of their partner's MV is related to that partner's behavior and their own RS. To this aim, we investigated the relationship between these variables on a sample of 178 couples. Our results showed that benefit-inducing strategies were used more by--and towards--partners of higher MV, and were positively connected with RS. Cost-inflicting strategies were more used by--and towards--partners of lower MV, and were negatively connected with RS. Less MV difference was positively correlated with RS and benefiting strategies, and negatively correlated with cost-inflicting strategies. It seems that good mates use strategies that benefit their partners, which, in turn, make them more valuable and, consequently, their partner more satisfied.
Retention of iron by infants.

PubMed

Fomon, S J; Nelson, S E; Ziegler, E E

2000-01-01

Throughout the world, the most common nutritional deficiency disorder of infants is iron deficiency. Developing effective strategies for preventing iron deficiency requires detailed knowledge of iron retention under ordinary living conditions. For the adult population, such knowledge is at an advanced stage, but relatively little is known about infants. Many reports of iron retention by infants have been based on the assumption that, as in normal and iron-deficient adults, 80%-100% of newly absorbed iron is promptly incorporated into circulating erythrocytes, but this assumption is not supported by available data. This communication presents a review of iron retention by term and preterm infants, as determined by metabolic balance studies or (59)Fe whole-body counting studies, and it explores the relationship between iron retention and postnatal age, iron nutritional status, iron intake (or dose), and type of feeding.
Comparative Analysis of Pharmacophore Features and Quantitative Structure-Activity Relationships for CD38 Covalent and Non-covalent Inhibitors.

PubMed

Zhang, Shuang; Xue, Xiwen; Zhang, Liangren; Zhang, Lihe; Liu, Zhenming

2015-12-01

In the past decade, the discovery, synthesis, and evaluation for hundreds of CD38 covalent and non-covalent inhibitors has been reported sequentially by our group and partners; however, a systematic structure-based guidance is still lacking for rational design of CD38 inhibitor. Here, we carried out a comparative analysis of pharmacophore features and quantitative structure-activity relationships for CD38 inhibitors. The results uncover that the essential interactions between key residues and covalent/non-covalent CD38 inhibitors include (i) hydrogen bond and hydrophobic interactions with residues Glu226 and Trp125, (ii) electrostatic or hydrogen bond interaction with the positively charged residue Arg127 region, and (iii) the hydrophobic interaction with residue Trp189. For covalent inhibitors, besides the covalent effect with residue Glu226, the electrostatic interaction with residue Arg127 is also necessary, while another hydrogen/non-bonded interaction with residues Trp125 and Trp189 can also be detected. By means of the SYBYL multifit alignment function, the best CoMFA and CoMSIA with CD38 covalent inhibitors presented cross-validated correlation coefficient values (q(2)) of 0.564 and 0.571, and non-cross-validated values (r(2)) of 0.967 and 0.971, respectively. The CD38 non-covalent inhibitors can be classified into five groups according to their chemical scaffolds, and the residues Glu226, Trp189, and Trp125 are indispensable for those non-covalent inhibitors binding to CD38, while the residues Ser126, Arg127, Asp155, Thr221, and Phe222 are also important. The best CoMFA and CoMSIA with the F12 analogues presented cross-validated correlation coefficient values (q(2)) of 0.469 and 0.454, and non-cross-validated values (r(2)) of 0.814 and 0.819, respectively. © 2015 John Wiley & Sons A/S.
Mate Value Discrepancy and Mate Retention Behaviors of Self and Partner.

PubMed

Sela, Yael; Mogilski, Justin K; Shackelford, Todd K; Zeigler-Hill, Virgil; Fink, Bernhard

2017-10-01

This study investigated the relationship between perceived mate value discrepancy (i.e., the difference between an individual's mate value and their partner's mate value) and perceived frequency of mate retention performed by an individual relative to his or her partner. In two studies, participants in long-term, exclusive, sexual, heterosexual relationships reported their own, and their partner's, mate value and mate retention. Samples included 899 community members (Study 1) and 941 students and community members (Study 2). In Study 1, we documented that individuals with higher self-perceived short-term mate value, and who perceive their partner to have lower (vs. higher) short-term mate value, perform less frequent Benefit-Provisioning mate retention, controlling for the partner's Benefit-Provisioning mate retention. In Study 2, we documented that individuals who perceive that they could less easily replace their partner, and who perceive their partner could more (vs. less) easily replace them, perform more frequent mate retention (Benefit-Provisioning and Cost-Inflicting), controlling for the partner's mate retention. These results highlight the importance of assessing perceived discrepancies in mate value (notably, regarding the replaceability of self and partner with another long-term mate) and perceived mate retention behaviors of self, relative to partner, between men and women in long-term relationships. © 2016 Wiley Periodicals, Inc.
Three-dimensional quantitative structure-activity relationship analysis for human pregnane X receptor for the prediction of CYP3A4 induction in human hepatocytes: structure-based comparative molecular field analysis.

PubMed

Handa, Koichi; Nakagome, Izumi; Yamaotsu, Noriyuki; Gouda, Hiroaki; Hirono, Shuichi

2015-01-01

The pregnane X receptor [PXR (NR1I2)] induces the expression of xenobiotic metabolic genes and transporter genes. In this study, we aimed to establish a computational method for quantifying the enzyme-inducing potencies of different compounds via their ability to activate PXR, for the application in drug discovery and development. To achieve this purpose, we developed a three-dimensional quantitative structure-activity relationship (3D-QSAR) model using comparative molecular field analysis (CoMFA) for predicting enzyme-inducing potencies, based on computer-ligand docking to multiple PXR protein structures sampled from the trajectory of a molecular dynamics simulation. Molecular mechanics-generalized born/surface area scores representing the ligand-protein-binding free energies were calculated for each ligand. As a result, the predicted enzyme-inducing potencies for compounds generated by the CoMFA model were in good agreement with the experimental values. Finally, we concluded that this 3D-QSAR model has the potential to predict the enzyme-inducing potencies of novel compounds with high precision and therefore has valuable applications in the early stages of the drug discovery process. © 2014 Wiley Periodicals, Inc. and the American Pharmacists Association.
Activation of a camptothecin prodrug by specific carboxylesterases as predicted by quantitative structure-activity relationship and molecular docking studies.

PubMed

Yoon, Kyoung Jin P; Krull, Erik J; Morton, Christopher L; Bornmann, William G; Lee, Richard E; Potter, Philip M; Danks, Mary K

2003-11-01

7-Ethyl-10-[4-(1-piperidino)-1-piperidino]carbonyloxycamptothecin (irinotecan, CPT-11) is a camptothecin prodrug that is metabolized by carboxylesterases (CE) to the active metabolite 7-ethyl-10-hydroxycamptothecin (SN-38), a topoisomerase I inhibitor. CPT-11 has shown encouraging antitumor activity against a broad spectrum of tumor types in early clinical trials, but hematopoietic and gastrointestinal toxicity limit its administration. To increase the therapeutic index of CPT-11 and to develop other prodrug analogues for enzyme/prodrug gene therapy applications, our laboratories propose to develop camptothecin prodrugs that will be activated by specific CEs. Specific analogues might then be predicted to be activated, for example, predominantly by human liver CE(hCE1), by human intestinal CE (hiCE), or in gene therapy approaches using a rabbit liver CE (rCE). This study describes a molecular modeling approach to relate the structure of rCE-activated camptothecin prodrugs with their biological activation. Comparative molecular field analysis, comparative molecular similarity index analysis, and docking studies were used to predict the biological activity of a 4-benzylpiperazine derivative of CPT-11 [7-ethyl-10-[4-(1-benzyl)-1-piperazino]carbonyloxycamptothecin (BP-CPT)] in U373MG glioma cell lines transfected with plasmids encoding rCE or hiCE. BP-CPT has been reported to be activated more efficiently than CPT-11 by a rat serum esterase activity; however, three-dimensional quantitative structure-activity relationship studies predicted that rCE would activate BP-CPT less efficiently than CPT-11. This was confirmed by both growth inhibition experiments and kinetic studies. The method is being used to design camptothecin prodrugs predicted to be activated by specific CEs.
Retention in Collegiate Aviation

DOT National Transportation Integrated Search

1996-01-01

Retention issues are important to people in all aspects of business and academia. The relationship of how many people start a project and how many actually complete it is an important one, regardless whether the project is an academic degree or a bus...
Three-dimensional quantitative structure-activity relationship modeling of cocaine binding by a novel human monoclonal antibody.

PubMed

Paula, Stefan; Tabet, Michael R; Farr, Carol D; Norman, Andrew B; Ball, W James

2004-01-01

Human monoclonal antibodies (mAbs) designed for immunotherapy have a high potential for avoiding the complications that may result from human immune system responses to the introduction of nonhuman mAbs into patients. This study presents a characterization of cocaine/antibody interactions that determine the binding properties of the novel human sequence mAb 2E2 using three-dimensional quantitative structure-activity relationship (3D-QSAR) methodology. We have experimentally determined the binding affinities of mAb 2E2 for cocaine and 38 cocaine analogues. The K(d) of mAb 2E2 for cocaine was 4 nM, indicating a high affinity. Also, mAb 2E2 displayed good cocaine specificity, as reflected in its 10-, 1500-, and 25000-fold lower binding affinities for the three physiologically relevant cocaine metabolites benzoylecgonine, ecgonine methyl ester, and ecgonine, respectively. 3D-QSAR models of cocaine binding were developed by comparative molecular similarity index analysis (CoMSIA). A model of high statistical quality was generated showing that cocaine binds to mAb 2E2 in a sterically restricted binding site that leaves the methyl group attached to the ring nitrogen of cocaine solvent-exposed. The methyl ester group of cocaine appears to engage in attractive van der Waals interactions with mAb 2E2, whereas the phenyl group contributes to the binding primarily via hydrophobic interactions. The model further indicated that an increase in partial positive charge near the nitrogen proton and methyl ester carbonyl group enhances binding affinity and that the ester oxygen likely forms an intermolecular hydrogen bond with mAb 2E2. Overall, the cocaine binding properties of mAb 2E2 support its clinical potential for development as a treatment of cocaine overdose and addiction.
Assessment of quantitative structure-activity relationship of toxicity prediction models for Korean chemical substance control legislation

PubMed Central

Kim, Kwang-Yon; Shin, Seong Eun; No, Kyoung Tai

2015-01-01

Objectives For successful adoption of legislation controlling registration and assessment of chemical substances, it is important to obtain sufficient toxicological experimental evidence and other related information. It is also essential to obtain a sufficient number of predicted risk and toxicity results. Particularly, methods used in predicting toxicities of chemical substances during acquisition of required data, ultimately become an economic method for future dealings with new substances. Although the need for such methods is gradually increasing, the-required information about reliability and applicability range has not been systematically provided. Methods There are various representative environmental and human toxicity models based on quantitative structure-activity relationships (QSAR). Here, we secured the 10 representative QSAR-based prediction models and its information that can make predictions about substances that are expected to be regulated. We used models that predict and confirm usability of the information expected to be collected and submitted according to the legislation. After collecting and evaluating each predictive model and relevant data, we prepared methods quantifying the scientific validity and reliability, which are essential conditions for using predictive models. Results We calculated predicted values for the models. Furthermore, we deduced and compared adequacies of the models using the Alternative non-testing method assessed for Registration, Evaluation, Authorization, and Restriction of Chemicals Substances scoring system, and deduced the applicability domains for each model. Additionally, we calculated and compared inclusion rates of substances expected to be regulated, to confirm the applicability. Conclusions We evaluated and compared the data, adequacy, and applicability of our selected QSAR-based toxicity prediction models, and included them in a database. Based on this data, we aimed to construct a system that can be used
Principal Support Is Imperative to the Retention of Teachers in Hard-to-Staff Schools

ERIC Educational Resources Information Center

Hughes, Amy L; Matt, John J.; O'Reilly, Frances L.

2015-01-01

Teacher retention is an ongoing problem in hard-to-staff schools. This research examined the relationship between principal support and retention of teachers in hard-to-staff schools. The purpose of this study was to, (a) to determine the relationship between teacher retention and principal support, (b) to examine the perception of support between…
Dietary flavonoids modulate CYP2C to improve drug oral bioavailability and their qualitative/quantitative structure-activity relationship.

PubMed

Wang, Hong-Jaan; Pao, Li-Heng; Hsiong, Cheng-Huei; Shih, Tung-Yuan; Lee, Meei-Shyuan; Hu, Oliver Yoa-Pu

2014-03-01

This study aims to improve the drug oral bioavailability by co-administration with flavonoid inhibitors of the CYP2C isozyme and to establish qualitative and quantitative (QSAR) structure-activity relationships (SAR) between flavonoids and CYP2C. A total of 40 naturally occurring flavonoids were screened in vitro for CYP2C inhibition. Enzyme activity was determined by measuring conversion of tolbutamide to 4-hydroxytolbutamide by rat liver microsomes. The percent inhibition and IC50 of each flavonoid were calculated and used to develop SAR and QSAR. The most effective flavonoid was orally co-administered in vivo with a cholesterol-reducing drug, fluvastatin, which is normally metabolized by CYP2C. The most potent CYP2C inhibitor identified in vitro was tamarixetin (IC50 = 1.4 μM). This flavonoid enhanced the oral bioavailability of fluvastatin in vivo, producing a >2-fold increase in the area under the concentration-time curve and in the peak plasma concentration. SAR analysis indicated that the presence of a 2,3-double bond in the C ring, hydroxylation at positions 5, 6, and 7, and glycosylation had important effects on flavonoid-CYP2C interactions. These findings should prove useful for predicting the inhibition of CYP2C activity by other untested flavonoid-like compounds. In the present study, tamarixetin significantly inhibited CYP2C activity in vitro and in vivo. Thus, the use of tamarixetin could improve the therapeutic efficacy of drugs with low bioavailability.
Student Retention and Persistence: A Quantitative Study of the Relationship of Non-Academic Barriers on Community College Students in Northern New York

ERIC Educational Resources Information Center

Troester-Trate, Katy Elizabeth

2017-01-01

As higher education enrollment patterns have changed, so too has the focus for institutional administrators. The community schools model is currently being piloted in New York State in an effort to increase the bleak retention and persistence rates of community college students. College students have been shown to be retained at higher rates when…
Structured Activities in Perceptual Training to Aid Retention of Visual and Auditory Images.

ERIC Educational Resources Information Center

Graves, James W.; And Others

The experimental program in structured activities in perceptual training was said to have two main objectives: to train children in retention of visual and auditory images and to increase the children's motivation to learn. Eight boys and girls participated in the program for two hours daily for a 10-week period. The age range was 7.0 to 12.10…
Evaluation of a quantitative structure-property relationship (QSPR) for predicting mid-visible refractive index of secondary organic aerosol (SOA).

PubMed

Redmond, Haley; Thompson, Jonathan E

2011-04-21

In this work we describe and evaluate a simple scheme by which the refractive index (λ = 589 nm) of non-absorbing components common to secondary organic aerosols (SOA) may be predicted from molecular formula and density (g cm(-3)). The QSPR approach described is based on three parameters linked to refractive index-molecular polarizability, the ratio of mass density to molecular weight, and degree of unsaturation. After computing these quantities for a training set of 111 compounds common to atmospheric aerosols, multi-linear regression analysis was conducted to establish a quantitative relationship between the parameters and accepted value of refractive index. The resulting quantitative relationship can often estimate refractive index to ±0.01 when averaged across a variety of compound classes. A notable exception is for alcohols for which the model consistently underestimates refractive index. Homogenous internal mixtures can conceivably be addressed through use of either the volume or mole fraction mixing rules commonly used in the aerosol community. Predicted refractive indices reconstructed from chemical composition data presented in the literature generally agree with previous reports of SOA refractive index. Additionally, the predicted refractive indices lie near measured values we report for λ = 532 nm for SOA generated from vapors of α-pinene (R.I. 1.49-1.51) and toluene (R.I. 1.49-1.50). We envision the QSPR method may find use in reconstructing optical scattering of organic aerosols if mass composition data is known. Alternatively, the method described could be incorporated into in models of organic aerosol formation/phase partitioning to better constrain organic aerosol optical properties.
Parabolic quantitative structure-activity relationships and photodynamic therapy: application of a three-compartment model with clearance to the in vivo quantitative structure-activity relationships of a congeneric series of pyropheophorbide derivatives used as photosensitizers for photodynamic therapy.

PubMed

Potter, W R; Henderson, B W; Bellnier, D A; Pandey, R K; Vaughan, L A; Weishaupt, K R; Dougherty, T J

1999-11-01

An open three-compartment pharmacokinetic model was applied to the in vivo quantitative structure-activity relationship (QSAR) data of a homologous series of pyropheophorbide photosensitizers for photodynamic therapy (PDT). The physical model was a lipid compartment sandwiched between two identical aqueous compartments. The first compartment was assumed to clear irreversibly at a rate K0. The measured octanol-water partition coefficients, P(i) (where i is the number of carbons in the alkyl chain) and the clearance rate K0 determined the clearance kinetics of the drugs. Solving the coupled differential equations of the three-compartment model produced clearance kinetics for each of the sensitizers in each of the compartments. The third compartment was found to contain the target of PDT. This series of compounds is quite lipophilic. Therefore these drugs are found mainly in the second compartment. The drug level in the third compartment represents a small fraction of the tissue level and is thus not accessible to direct measurement by extraction. The second compartment of the model accurately predicted the clearance from the serum of mice of the hexyl ether of pyropheophorbide a, one member of this series of compounds. The diffusion and clearance rate constants were those found by fitting the pharmacokinetics of the third compartment to the QSAR data. This result validated the magnitude and mechanistic significance of the rate constants used to model the QSAR data. The PDT response to dose theory was applied to the kinetic behavior of the target compartment drug concentration. This produced a pharmacokinetic-based function connecting PDT response to dose as a function of time postinjection. This mechanistic dose-response function was fitted to published, single time point QSAR data for the pheophorbides. As a result, the PDT target threshold dose together with the predicted QSAR as a function of time postinjection was found.

Structure-activity relationships between sterols and their thermal stability in oil matrix.

PubMed

Hu, Yinzhou; Xu, Junli; Huang, Weisu; Zhao, Yajing; Li, Maiquan; Wang, Mengmeng; Zheng, Lufei; Lu, Baiyi

2018-08-30

Structure-activity relationships between 20 sterols and their thermal stabilities were studied in a model oil system. All sterol degradations were found to be consistent with a first-order kinetic model with determination of coefficient (R 2 ) higher than 0.9444. The number of double bonds in the sterol structure was negatively correlated with the thermal stability of sterol, whereas the length of the branch chain was positively correlated with the thermal stability of sterol. A quantitative structure-activity relationship (QSAR) model to predict thermal stability of sterol was developed by using partial least squares regression (PLSR) combined with genetic algorithm (GA). A regression model was built with R 2 of 0.806. Almost all sterol degradation constants can be predicted accurately with R 2 of cross-validation equals to 0.680. Four important variables were selected in optimal QSAR model and the selected variables were observed to be related with information indices, RDF descriptors, and 3D-MoRSE descriptors. Copyright © 2018 Elsevier Ltd. All rights reserved.
Job embeddedness and nurse retention.

PubMed

Reitz, O Ed; Anderson, Mary Ann; Hill, Pamela D

2010-01-01

Nurse retention is a different way of conceptualizing the employer-employee relationship when compared with turnover. Job embeddedness (JE), a construct based on retention, represents the sum of reasons why employees remain at their jobs. However, JE has not been investigated in relation to locale (urban or rural) or exclusively with a sample of registered nurses (RNs). The purpose of this study was to determine what factors (JE, age, gender, locale, and income) help predict nurse retention. A cross-sectional mailed survey design was used with RNs in different locales (urban or rural). Job embeddedness was measured by the score on the composite, standardized instrument. Nurse retention was measured by self-report items concerning intent to stay. A response rate of 49.3% was obtained. The typical respondent was female (96.1%), white, non-Hispanic (87.4%), and married (74.9%). Age and JE were predictive of nurse retention and accounted for 26% of the explained variance in intent to stay. Although age was a significant predictor of intent to stay, it accounted for only 1.4% of the variance while JE accounted for 24.6% of the variance of nurse retention (as measured by intent to stay). Older, more "embedded" nurses are more likely to remain employed in their current organization. Based on these findings, JE may form the basis for the development of an effective nurse retention program.
Linear and non-linear quantitative structure-activity relationship models on indole substitution patterns as inhibitors of HIV-1 attachment.

PubMed

Nirouei, Mahyar; Ghasemi, Ghasem; Abdolmaleki, Parviz; Tavakoli, Abdolreza; Shariati, Shahab

2012-06-01

The antiviral drugs that inhibit human immunodeficiency virus (HIV) entry to the target cells are already in different phases of clinical trials. They prevent viral entry and have a highly specific mechanism of action with a low toxicity profile. Few QSAR studies have been performed on this group of inhibitors. This study was performed to develop a quantitative structure-activity relationship (QSAR) model of the biological activity of indole glyoxamide derivatives as inhibitors of the interaction between HIV glycoprotein gp120 and host cell CD4 receptors. Forty different indole glyoxamide derivatives were selected as a sample set and geometrically optimized using Gaussian 98W. Different combinations of multiple linear regression (MLR), genetic algorithms (GA) and artificial neural networks (ANN) were then utilized to construct the QSAR models. These models were also utilized to select the most efficient subsets of descriptors in a cross-validation procedure for non-linear log (1/EC50) prediction. The results that were obtained using GA-ANN were compared with MLR-MLR and MLR-ANN models. A high predictive ability was observed for the MLR, MLR-ANN and GA-ANN models, with root mean sum square errors (RMSE) of 0.99, 0.91 and 0.67, respectively (N = 40). In summary, machine learning methods were highly effective in designing QSAR models when compared to statistical method.
An in vivo quantitative structure-activity relationship for a congeneric series of pyropheophorbide derivatives as photosensitizers for photodynamic therapy.

PubMed

Henderson, B W; Bellnier, D A; Greco, W R; Sharma, A; Pandey, R K; Vaughan, L A; Weishaupt, K R; Dougherty, T J

1997-09-15

An in vivo quantitative structure-activity relationship (QSAR) study was carried out on a congeneric series of pyropheophorbide photosensitizers to identify structural features critical for their antitumor activity in photodynamic therapy (PDT). The structural elements evaluated in this study include the length and shape (alkyl, alkenyl, cyclic, and secondary analogs) of the ether side chain. C3H mice, harboring the radiation-induced fibrosarcoma tumor model, were used to study three biological response endpoints: tumor growth delay, tumor cell lethality, and vascular perfusion. All three endpoints revealed highly similar QSAR patterns that constituted a function of the alkyl ether chain length and drug lipophilicity, which is defined as the log of the octanol:water partition coefficient (log P). When the illumination of tumor, tumor cells, or cutaneous vasculature occurred 24 h after sensitizer administration, activities were minimal with analogs of log P < or = 5, increased dramatically between log P of 5-6, and peaked between log P of 5.6-6.6. Activities declined gradually with higher log P. The lack of activity of the least-lipophilic analogs was explained in large part by their poor biodistribution characteristics, which yielded negligible tumor and plasma drug levels at the time of treatment with light. The progressively lower potencies of the most lipophilic analogs cannot be explained through the overall tumor and plasma pharmacokinetics of photosensitizer because tumor and plasma concentrations progressively increased with lipophilicity. When compensated for differences in tumor photosensitizer concentration, the 1-hexyl derivative (optimal lipophilicity) was 5-fold more potent than the 1-dodecyl derivative (more lipophilic) and 3-fold more potent than the 1-pentyl analog (less lipophilic), indicating that, in addition to the overall tumor pharmacokinetics, pharmacodynamic factors may influence PDT activity. Drug lipophilicity was highly predictive for
Conceptual development and retention within the learning cycle

NASA Astrophysics Data System (ADS)

McWhirter, Lisa Jo

1998-12-01

This research was designed to achieve two goals: (1) examine concept development and retention within the learning cycle and (2) examine how students' concept development is mediated by classroom discussions and the students' small cooperative learning group. Forty-eight sixth-grade students and one teacher at an urban middle school participated in the study. The research utilized both quantitative and qualitative analyses. Quantitative assessments included a concept mapping technique as well as teacher generated multiple choice tests. Preliminary quantitative analysis found that students' reading levels had an effect on students' pretest scores in both the concept mapping and the multiple-choice assessment. Therefore, a covariant design was implemented for the quantitative analyses. Quantitative analysis techniques were used to examine concept development and retention, it was discovered that the students' concept knowledge increased significantly from the time of the conclusion of the term introduction phase to the conclusion of the expansion phase. These findings would indicate that all three phases of the learning cycle are necessary for conceptual development. However, quantitative analyses of concept maps indicated that this is not true for all students. Individual students showed evidence of concept development and integration at each phase. Therefore, concept development is individualized and all phases of the learning cycle are not necessary for all students. As a result, individual's assimilation, disequilibration, accommodation and organization may not correlate with the phases of the learning cycle. Quantitative analysis also indicated a significant decrease in the retention of concepts over time. Qualitative analyses were used to examine how students' concept development is mediated by classroom discussions and the students' small cooperative learning group. It was discovered that there was a correlation between teacher-student interaction and small
Prediction of local proximal tibial subchondral bone structural stiffness using subject-specific finite element modeling: Effect of selected density-modulus relationship.

PubMed

Nazemi, S Majid; Amini, Morteza; Kontulainen, Saija A; Milner, Jaques S; Holdsworth, David W; Masri, Bassam A; Wilson, David R; Johnston, James D

2015-08-01

Quantitative computed tomography based subject-specific finite element modeling has potential to clarify the role of subchondral bone alterations in knee osteoarthritis initiation, progression, and pain initiation. Calculation of bone elastic moduli from image data is a basic step when constructing finite element models. However, different relationships between elastic moduli and imaged density (known as density-modulus relationships) have been reported in the literature. The objective of this study was to apply seven different trabecular-specific and two cortical-specific density-modulus relationships from the literature to finite element models of proximal tibia subchondral bone, and identify the relationship(s) that best predicted experimentally measured local subchondral structural stiffness with highest explained variance and least error. Thirteen proximal tibial compartments were imaged via quantitative computed tomography. Imaged bone mineral density was converted to elastic moduli using published density-modulus relationships and mapped to corresponding finite element models. Proximal tibial structural stiffness values were compared to experimentally measured stiffness values from in-situ macro-indentation testing directly on the subchondral bone surface (47 indentation points). Regression lines between experimentally measured and finite element calculated stiffness had R(2) values ranging from 0.56 to 0.77. Normalized root mean squared error varied from 16.6% to 337.6%. Of the 21 evaluated density-modulus relationships in this study, Goulet combined with Snyder and Schneider or Rho appeared most appropriate for finite element modeling of local subchondral bone structural stiffness. Though, further studies are needed to optimize density-modulus relationships and improve finite element estimates of local subchondral bone structural stiffness. Copyright © 2015 Elsevier Ltd. All rights reserved.
The Importance of Factors Related to Nurse Retention: Using the Baptist Health Nurse Retention Questionnaire, Part 2.

PubMed

Bugajski, Andrew; Lengerich, Alex; Marchese, Matthew; Hall, Brittany; Yackzan, Susan; Davies, Claire; Brockopp, Dorothy

2017-06-01

The purpose of this study was to examine the importance of factors related to nurse retention. Retaining nurses within the healthcare system is a challenge for hospital administrators. Understanding factors important to nurse retention is essential. Responses of nurses (n = 279) to the Baptist Health Nurse Retention Questionnaire (BHNRQ) at a 391-bed Magnet® redesignated community hospital were analyzed to explore differences in importance scores of bedside nurses. The results demonstrate that each of the 12 items on the BHNRQ was moderately to highly important. A multivariate analysis of variance based on generation, degree, unit, and experience revealed no significant differences on subscale scores (nursing practice, management, and staffing). Themes derived from the comment section on the BHNRQ were consistent with quantitative findings. Clinical and managerial competence, engagement with their employees, and presence on the unit are keys to retaining a satisfied nursing workforce.
Biodestruction of strongly swelling polymer hydrogels and its effect on the water retention capacity of soils

NASA Astrophysics Data System (ADS)

Smagin, A. V.; Sadovnikova, N. B.; Smagina, M. V.

2014-06-01

The biodestruction of strongly swelling polymer hydrogels (water adsorbing soil conditioners of the new generation) has been studied at the quantitative level using original mathematical models. In laboratory experiments, a relationship between the hydrogel degradation rate and the temperature has been obtained, and the effect of the biodestruction on the water retention curve of soil compositions with hydrogels (used as an index of their water retention capacity) has been assessed. From the automatic monitoring data of the temperature regime of soils, the potential biodestruction of hydrogels has been predicted for different climatic conditions. The loss of hydrogels during three months of the vegetation period because of destruction can exceed 30% of their initial content in irrigated agriculture under arid climatic conditions and more than 10% under humid climatic conditions. Thus, the biodestruction of hydrogels is one of the most important factors decreasing their efficiency under actual soil conditions.
Quantitative Methods in Psychology: Inevitable and Useless

PubMed Central

Toomela, Aaro

2010-01-01

Science begins with the question, what do I want to know? Science becomes science, however, only when this question is justified and the appropriate methodology is chosen for answering the research question. Research question should precede the other questions; methods should be chosen according to the research question and not vice versa. Modern quantitative psychology has accepted method as primary; research questions are adjusted to the methods. For understanding thinking in modern quantitative psychology, two epistemologies should be distinguished: structural-systemic that is based on Aristotelian thinking, and associative-quantitative that is based on Cartesian–Humean thinking. The first aims at understanding the structure that underlies the studied processes; the second looks for identification of cause–effect relationships between the events with no possible access to the understanding of the structures that underlie the processes. Quantitative methodology in particular as well as mathematical psychology in general, is useless for answering questions about structures and processes that underlie observed behaviors. Nevertheless, quantitative science is almost inevitable in a situation where the systemic-structural basis of behavior is not well understood; all sorts of applied decisions can be made on the basis of quantitative studies. In order to proceed, psychology should study structures; methodologically, constructive experiments should be added to observations and analytic experiments. PMID:21833199
Quantitative methods in psychology: inevitable and useless.

PubMed

Toomela, Aaro

2010-01-01

Science begins with the question, what do I want to know? Science becomes science, however, only when this question is justified and the appropriate methodology is chosen for answering the research question. Research question should precede the other questions; methods should be chosen according to the research question and not vice versa. Modern quantitative psychology has accepted method as primary; research questions are adjusted to the methods. For understanding thinking in modern quantitative psychology, two epistemologies should be distinguished: structural-systemic that is based on Aristotelian thinking, and associative-quantitative that is based on Cartesian-Humean thinking. The first aims at understanding the structure that underlies the studied processes; the second looks for identification of cause-effect relationships between the events with no possible access to the understanding of the structures that underlie the processes. Quantitative methodology in particular as well as mathematical psychology in general, is useless for answering questions about structures and processes that underlie observed behaviors. Nevertheless, quantitative science is almost inevitable in a situation where the systemic-structural basis of behavior is not well understood; all sorts of applied decisions can be made on the basis of quantitative studies. In order to proceed, psychology should study structures; methodologically, constructive experiments should be added to observations and analytic experiments.
Comparison of the applicability domain of a quantitative structure-activity relationship for estrogenicity with a large chemical inventory.

PubMed

Netzeva, Tatiana I; Gallegos Saliner, Ana; Worth, Andrew P

2006-05-01

The aim of the present study was to illustrate that it is possible and relatively straightforward to compare the domain of applicability of a quantitative structure-activity relationship (QSAR) model in terms of its physicochemical descriptors with a large inventory of chemicals. A training set of 105 chemicals with data for relative estrogenic gene activation, obtained in a recombinant yeast assay, was used to develop the QSAR. A binary classification model for predicting active versus inactive chemicals was developed using classification tree analysis and two descriptors with a clear physicochemical meaning (octanol-water partition coefficient, or log Kow, and the number of hydrogen bond donors, or n(Hdon)). The model demonstrated a high overall accuracy (90.5%), with a sensitivity of 95.9% and a specificity of 78.1%. The robustness of the model was evaluated using the leave-many-out cross-validation technique, whereas the predictivity was assessed using an artificial external test set composed of 12 compounds. The domain of the QSAR training set was compared with the chemical space covered by the European Inventory of Existing Commercial Chemical Substances (EINECS), as incorporated in the CDB-EC software, in the log Kow / n(Hdon) plane. The results showed that the training set and, therefore, the applicability domain of the QSAR model covers a small part of the physicochemical domain of the inventory, even though a simple method for defining the applicability domain (ranges in the descriptor space) was used. However, a large number of compounds are located within the narrow descriptor window.
Structure- and ligand-based structure-activity relationships for a series of inhibitors of aldolase.

PubMed

Ferreira, Leonardo G; Andricopulo, Adriano D

2012-12-01

Aldolase has emerged as a promising molecular target for the treatment of human African trypanosomiasis. Over the last years, due to the increasing number of patients infected with Trypanosoma brucei, there is an urgent need for new drugs to treat this neglected disease. In the present study, two-dimensional fragment-based quantitative-structure activity relationship (QSAR) models were generated for a series of inhibitors of aldolase. Through the application of leave-one-out and leave-many-out cross-validation procedures, significant correlation coefficients were obtained (r²=0.98 and q²=0.77) as an indication of the statistical internal and external consistency of the models. The best model was employed to predict pKi values for a series of test set compounds, and the predicted values were in good agreement with the experimental results, showing the power of the model for untested compounds. Moreover, structure-based molecular modeling studies were performed to investigate the binding mode of the inhibitors in the active site of the parasitic target enzyme. The structural and QSAR results provided useful molecular information for the design of new aldolase inhibitors within this structural class.
Quantitative structure-activity relationship study of antioxidative peptide by using different sets of amino acids descriptors

NASA Astrophysics Data System (ADS)

Li, Yao-Wang; Li, Bo; He, Jiguo; Qian, Ping

2011-07-01

A database consisting of 214 tripeptides which contain either His or Tyr residue was applied to study quantitative structure-activity relationships (QSAR) of antioxidative tripeptides. Partial Least-Squares Regression analysis (PLSR) was conducted using parameters individually of each amino acid descriptor, including Divided Physico-chemical Property Scores (DPPS), Hydrophobic, Electronic, Steric, and Hydrogen (HESH), Vectors of Hydrophobic, Steric, and Electronic properties (VHSE), Molecular Surface-Weighted Holistic Invariant Molecular (MS-WHIM), isotropic surface area-electronic charge index (ISA-ECI) and Z-scale, to describe antioxidative tripeptides as X-variables and antioxidant activities measured with ferric thiocyanate methods were as Y-variable. After elimination of outliers by Hotelling's T 2 method and residual analysis, six significant models were obtained describing the entire data set. According to cumulative squared multiple correlation coefficients ( R2), cumulative cross-validation coefficients ( Q2) and relative standard deviation for calibration set (RSD c), the qualities of models using DPPS, HESH, ISA-ECI, and VHSE descriptors are better ( R2 > 0.6, Q2 > 0.5, RSD c < 0.39) than that of models using MS-WHIM and Z-scale descriptors ( R2 < 0.6, Q2 < 0.5, RSD c > 0.44). Furthermore, the predictive ability of models using DPPS descriptor is best among the six descriptors systems (cumulative multiple correlation coefficient for predict set ( Rext2) > 0.7). It was concluded that the DPPS is better to describe the amino acid of antioxidative tripeptides. The results of DPPS descriptor reveal that the importance of the center amino acid and the N-terminal amino acid are far more than the importance of the C-terminal amino acid for antioxidative tripeptides. The hydrophobic (positively to activity) and electronic (negatively to activity) properties of the N-terminal amino acid are suggested to play the most important significance to activity, followed
Newly Licensed RN Retention: Hospital and Nurse Characteristics.

PubMed

Blegen, Mary A; Spector, Nancy; Lynn, Mary R; Barnsteiner, Jane; Ulrich, Beth T

2017-10-01

The aims of this study were to examine the relationship between 1-year retention of newly licensed RNs (NLRNs) employed in hospitals and personal and hospital characteristics, and determine which characteristics had the most influence. A secondary analysis of data collected in a study of transition to practice was used to describe the retention of 1464 NLRNs employed by 97 hospitals in 3 states. Hospitals varied in size, location (urban and rural), Magnet® designation, and university affiliation. The NLRNs also varied in education, age, race, gender, and experience. The overall retention rate at 1 year was 83%. Retention of NLRNs was higher in urban areas and in Magnet hospitals. The only personal characteristic that affected retention was age, with younger nurses more likely to stay. Hospital characteristics had a larger effect on NLRN retention than personal characteristics. Hospitals in rural areas have a particular challenge in retaining NLRNs.
Quantitative assessment of the relationship between biomarker content and biomass in marine phytoplankton in responses to temperature and nutrient supply ratio changes

NASA Astrophysics Data System (ADS)

Ding, Y.; Chen, X.; Bi, R.; Zhang, L. H.; Li, L.; Zhao, M.

2016-12-01

Alkenones and sterols are useful biomarkers to construct past productivity and community structure changes in aquatic environments. Until now, the quantitative relationship between biomarker content and biomass in marine phytoplankton remains understudied, which hinders the quantitative reconstruction of ocean changes. In this study, we carried out laboratory culture experiments to determine the quantitative relationship between biomarker content and biomass under three temperatures (15°, 20° and 25°) and three N:P supply ratios (N:P=10:1, 24:1 and 63:1 mol mol-1) for three common phytoplankton groups, diatoms (Phaeodactylum tricornutum Bohlin, Skeletonema costatum, Chaetoceros muelleri), dinoflagellates (Karenia mikimotoi, Prorocentrum donghaiense, Prorocentrum minimum), and coccolithophores (Emiliania huxleyi). Alkenones were only detected in E. huxleyiand dinosterol was only detected in dinoflagellates, confirming that they are the biomarkers for these two groups of phytoplankton, respectively. Brassicasterol was detected in all three groups of phytoplankton, but its content was higher in diatoms, suggesting that it is still a useful biomarker for diatoms. Cell-normalized alkenone content (pg/cell) increases with increasing growth temperature by up to 30%; while the effect of nutrients on alkenone content is minimum. On the other hand, cell-normalized dinosterol content is not temperature dependent, but it is strongly affected by nutrient ratio changes. The effects of temperature and nutrients on cell-normalized brassicasterol content are phytoplankton dependent. For diatoms, the temperature effect is minimum while the nutrient effect is significant but also varies with temperatures. Our results have strong implications for understanding how different phytoplankton respond to global changes, and for more quantitative reconstruction of past productivity and community structure changes using these biomarkers.
Generation of accurate peptide retention data for targeted and data independent quantitative LC-MS analysis: Chromatographic lessons in proteomics.

PubMed

Krokhin, Oleg V; Spicer, Vic

2016-12-01

The emergence of data-independent quantitative LC-MS/MS analysis protocols further highlights the importance of high-quality reproducible chromatographic procedures. Knowing, controlling and being able to predict the effect of multiple factors that alter peptide RP-HPLC separation selectivity is critical for successful data collection for the construction of ion libraries. Proteomic researchers have often regarded RP-HPLC as a "black box", while vast amount of research on peptide separation is readily available. In addition to obvious parameters, such as the type of ion-pairing modifier, stationary phase and column temperature, we describe the "mysterious" effects of gradient slope, column size and flow rate on peptide separation selectivity. Retention time variations due to these parameters are governed by the linear solvent strength (LSS) theory on a peptide level by the value of its slope S in the basic LSS equation-a parameter that can be accurately predicted. Thus, the application of shallower gradients, higher flow rates, or smaller columns will each increases the relative retention of peptides with higher S-values (long species with multiple positively charged groups). Simultaneous changes to these parameters that each drive shifts in separation selectivity in the same direction should be avoided. The unification of terminology represents another pressing issue in this field of applied proteomics that should be addressed to facilitate further progress. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
The Relationship between SAT Scores and Retention to the Second Year: Replication with 2009 SAT Validity Sample. Statistical Report 2011-3

ERIC Educational Resources Information Center

Mattern, Krista D.; Patterson, Brian F.

2012-01-01

The College Board formed a research consortium with four-year colleges and universities to build a national higher education database with the primary goal of validating the revised SAT for use in college admission. A study by Mattern and Patterson (2009) examined the relationship between SAT scores and retention to the second year of college. The…
Retention strategies in longitudinal studies with emerging adults.

PubMed

Hanna, Kathleen M; Scott, Linda L; Schmidt, Karen K

2014-01-01

The purpose of this report was to describe retention strategies that were useful and those that were not in a longitudinal study of emerging adults. A longitudinal study examining the transition to young adulthood among emerging adults with type 1 diabetes, which had success in retention, provided the context for describing retention strategies. A challenge in longitudinally designed studies is retention of participants because the loss decreases power for statistical analysis. Given that emerging adulthood is a period of instability, retention is particularly challenging among this population. However, longitudinal studies are the best way to understand developmental changes, and it is also important to increase our knowledge of health outcomes during emerging adulthood. Retention strategies used in the study are described, including promoting a positive relationship with participants, maintaining contact with participants, having a study staff with good interpersonal skills, using incentives, conveying respect for participants, and using user-friendly data collection. Useful strategies to promote a positive relationship included sending cards and newsletters to participants, maintaining consistency of contact person, and expressing appreciation for participant's time and effort. Useful strategies for maintaining contact with participants included obtaining contact information at every data collection point, maintaining birth dates and chart numbers in tracking databases, monitoring returned mail, and using Web search engines. Other useful strategies were providing incentives to participants, employing staff with good interpersonal skills, providing participants with choices when appropriate, and using user-friendly data collection. One strategy, using contests, was not found useful. Despite the challenges of conducting longitudinally designed studies with emerging adults, multiple retention strategies can be used that are useful to retention. It is feasible to
The impact of humanitarian context conditions and individual characteristics on aid worker retention.

PubMed

Korff, Valeska P; Balbo, Nicoletta; Mills, Melinda; Heyse, Liesbet; Wittek, Rafael

2015-07-01

High employee turnover rates constitute a major challenge to effective aid provision. This study examines how features of humanitarian work and aid workers' individual characteristics affect retention within one humanitarian organisation, Médecins Sans Frontières (MSF) Holland. The study extends existing research by providing new theoretical explanations of employment opportunities and constraints and by engaging in the first large-scale quantitative analysis of aid worker retention. Using a database of field staff (N=1,955), a logistic regression is performed of the likelihood of reenlistment after a first mission. The findings demonstrate that only 40 per cent of employees reenlist for a second mission with MSF Holland, and that workplace location and security situation, age, and gender have no significant effect. Individuals are less likely to reenlist if they returned early from the first mission for a personal reason, are in a relationship, are medical doctors, or if they come from highly developed countries. The paper reflects on the findings in the light of policy. © 2015 The Author(s). Disasters © Overseas Development Institute, 2015.
Abundance and population structure of eastern worm snakes in forest stands with various levels of overstory tree retention

Treesearch

Zachary I. Felix; Yong Wang; Callie Jo Schweitzer

2010-01-01

In-depth analyses of a speciesâ response to canopy retention treatments can provide insight into reasons for observed changes in abundance. The eastern worm snake (Carphophis amoenus amoenus Say) is common in many eastern deciduous forests, yet little is known about the ecology of the species in managed forests. We examined the relationship between...

Employee retention: a customer service approach.

PubMed

Gerson, Richard F

2002-01-01

techniques of this process mirror the activities of customer service and customer relationship management, I call the combined process C/ERM for customer/employee relationship management. Both activities must be going on simultaneously to create a loyalty link that ensures customer satisfaction and retention through employee service, satisfaction and retention.
Synthesis and quantitative structure activity relationship (QSAR) of arylidene (benzimidazol-1-yl)acetohydrazones as potential antibacterial agents.

PubMed

El-Kilany, Yeldez; Nahas, Nariman M; Al-Ghamdi, Mariam A; Badawy, Mohamed E I; El Ashry, El Sayed H

2015-01-01

Ethyl (benzimidazol-1-yl)acetate was subjected to hydrazinolysis with hydrazine hydrate to give (benzimidazol-1-yl)acetohydrazide. The latter was reacted with various aromatic aldehydes to give the respective arylidene (1H-benzimidazol-1-yl)acetohydrazones. Solutions of the prepared hydrazones were found to contain two geometric isomers. Similarly (2-methyl-benzimidazol-1-yl)acetohydrazide was reacted with various aldehydes to give the corresponding hydrazones. The antibacterial activity was evaluated in vitro by minimum inhibitory concentration (MIC) against Agrobacterium tumefaciens (A. tumefaciens), Erwinia carotovora (E. carotovora), Corynebacterium fascians (C. fascians) and Pseudomonas solanacearum (P. solanacearum). MIC result demonstrated that salicylaldehyde(1H-benzimidazol-1-yl)acetohydrazone (4) was the most active compound (MIC = 20, 35, 25 and 30 mg/L against A. tumefaciens, C. fascians, E. carotovora and P. solanacearum, respectively). Quantitative structure activity relationship (QSAR) investigation using Hansch analysis was applied to find out the correlation between antibacterial activity and physicochemical properties. Various physicochemical descriptors and experimentally determined MIC values for different microorganisms were used as independent and dependent variables, respectively. pMICs of the compounds exhibited good correlation (r = 0.983, 0.914, 0.960 and 0.958 for A. tumefaciens, C. fascians, E. carotovora and P. solanacearum, respectively) with the prediction made by the model. QSAR study revealed that the hydrophobic parameter (ClogP), the aqueous solubility (LogS), calculated molar refractivity, topological polar surface area and hydrogen bond acceptor were found to have overall significant correlation with antibacterial activity. The statistical results of training set, correlation coefficient (r and r (2)), the ratio between regression and residual variances (f, Fisher's statistic), the standard error of estimates and
A Predictive Statistical Model of Navy Career Enlisted Retention Behavior Utilizing Economic Variables.

DTIC Science & Technology

1980-12-01

career retention rates , and to predict future career retention rates in the Navy. The statistical model utilizes economic variables as predictors...The model developed r has a high correlation with Navy career retention rates . The problem of Navy career retention has not been adequately studied, 0D...findings indicate Navy policymakers must be cognizant of the relationships of economic factors to Navy career retention rates . Accrzsiofl ’or NTIS GRA&I
Quantitative Causal-Comparative Relationship between Interactive Whiteboard Instruction and Student Science Proficiency

ERIC Educational Resources Information Center

Danelczyk, Ewa Krystyna

2013-01-01

The purpose of this quantitative causal-comparative study was to investigate the relationship between the instructional effects of the interactive whiteboard and students' proficiency levels in eighth-grade science as evidenced by the state FCAT scores. A total of 46 eighth-grade science teachers in a South Florida public school district completed…
A Reinforcement-Based Learning Paradigm Increases Anatomical Learning and Retention-A Neuroeducation Study.

PubMed

Anderson, Sarah J; Hecker, Kent G; Krigolson, Olave E; Jamniczky, Heather A

2018-01-01

In anatomy education, a key hurdle to engaging in higher-level discussion in the classroom is recognizing and understanding the extensive terminology used to identify and describe anatomical structures. Given the time-limited classroom environment, seeking methods to impart this foundational knowledge to students in an efficient manner is essential. Just-in-Time Teaching (JiTT) methods incorporate pre-class exercises (typically online) meant to establish foundational knowledge in novice learners so subsequent instructor-led sessions can focus on deeper, more complex concepts. Determining how best do we design and assess pre-class exercises requires a detailed examination of learning and retention in an applied educational context. Here we used electroencephalography (EEG) as a quantitative dependent variable to track learning and examine the efficacy of JiTT activities to teach anatomy. Specifically, we examined changes in the amplitude of the N250 and reward positivity event-related brain potential (ERP) components alongside behavioral performance as novice students participated in a series of computerized reinforcement-based learning modules to teach neuroanatomical structures. We found that as students learned to identify anatomical structures, the amplitude of the N250 increased and reward positivity amplitude decreased in response to positive feedback. Both on a retention and transfer exercise when learners successfully remembered and translated their knowledge to novel images, the amplitude of the reward positivity remained decreased compared to early learning. Our findings suggest ERPs can be used as a tool to track learning, retention, and transfer of knowledge and that employing the reinforcement learning paradigm is an effective educational approach for developing anatomical expertise.
The Effects of Spatial Visualization Skill Training on Gender and Retention in Engineering.

ERIC Educational Resources Information Center

Devon, Richard; Engel, Renata; Turner, Geoffrey

1998-01-01

Engineering students were given a mental rotation test at the beginning and end of their first-year engineering course and again several years later to assess the relationship between spatial visualization skill and retention in engineering. No relationship was found between task scores and retention; however, a course in design and graphics…
Spatial Distribution of Overstory Retention Influences Resources and Growth of Longleaf Pine Seedlings

Treesearch

Brian Palik; Robert J. Mitchell; Stephen Pecot; Mike Battaglia; Mou Pu

2003-01-01

Increasingly, overstory retention is being used in forests traditionally managed for single-cohort structure. One rationale for retention is that residual stand structure better resembles the complex structure of forests after natural disturbance, helping to perpetuate ecosystem fuctions dependent on that structure. The benefits of retention come at the cost of reduced...
The Relationship between SAT® Scores and Retention to the Second Year: Replication with the 2010 SAT Validity Sample. Statistical Report 2013-1

ERIC Educational Resources Information Center

Mattern, Krista D.; Patterson, Brian F.

2013-01-01

The College Board formed a research consortium with four-year colleges and universities to build a national higher education database with the primary goal of validating the revised SAT for use in college admission. A study by Mattern and Patterson (2009) examined the relationship between SAT scores and retention to the second year. The sample…
[Systematic evaluation of retention behavior of carbohydrates in hydrophilic interaction liquid chromatography].

PubMed

Fu, Qing; Wang, Jun; Liang, Tu; Xu, Xiaoyong; Jin, Yu

2013-11-01

A systematic evaluation of retention behavior of carbohydrates in hydrophilic interaction liquid chromatography (HILIC) was performed. The influences of mobile phase, stationary phase and buffer salt on the retention of carbohydrates were investigated. According to the results, the retention time of carbohydrates decreased as the proportion of acetonitrile in mobile phase decreased. Increased time of carbohydrates was observed as the concentration of buffer salt in mobile phase increased. The retention behavior of carbohydrates was also affected by organic solvent and HILIC stationary phase. Furthermore, an appropriate retention equation was used in HILIC mode. The retention equation lnk = a + blnC(B) + cC(B) could quantitatively describe the retention factors of carbohydrates of plant origin with good accuracy: the relative error of the predicted time to actual time was less than 0.3%. The evaluation results could provide guidance for carbohydrates to optimize the experimental conditions in HILIC method development especially for carbohydrate separation
Registered nurse retention strategies in nursing homes: a two-factor perspective.

PubMed

Hunt, Selina R; Probst, Janice C; Haddock, Kathlyn S; Moran, Robert; Baker, Samuel L; Anderson, Ruth A; Corazzini, Kirsten

2012-01-01

As the American population ages and the proportion of individuals over the age of 65 expands, the demand for high-quality nursing home care will increase. However, nursing workforce instability threatens care quality and sustainability in this sector. Despite increasing attention to nursing home staff turnover, far less is known about registered nurse (RN) retention. In this study, the relationships between retention strategies, employee benefits, features of the practice environment, and RN retention were explored. Further, the utility of Herzberg's two-factor theory of motivation as a framework for nursing home retention studies was evaluated. This study was a secondary analysis of the nationally representative 2004 National Nursing Home Survey. The final sample of 1,174 participating nursing homes were either certified by Medicare or Medicaid or licensed by state agencies. We used a weighted multinomial logistic regression using an incremental approach to model the relationships. Although most nursing homes offered some combination of retention programs, the majority of strategies did not have a significant association with the level of RN retention reported by facilities. Director of nursing tenure and other extrinsic factors had the strongest association with RN retention in adjusted analyses. To improve RN retention, organizations may benefit greatly from stabilizing nursing home leadership, especially the director of nursing position. Second, managers of facilities with poor retention may consider adding career ladders for advancement, awarding attendance, and improving employee benefits. As a behavioral outcome of motivation and satisfaction, retention was not explained as expected using Herzberg's two-factor theory.
Recruitment and retention of rural African Americans in diabetes research: lessons learned.

PubMed

Loftin, Wanda Anderson; Barnett, Steven K; Bunn, Peggy Summers; Sullivan, Patra

2005-01-01

The purpose of this article was to describe lessons learned about recruitment and retention of rural African Americans from published literature, the authors' research, and research experience. Two rural, community-based research studies with African Americans with diabetes are used to illustrate different issues and strategies in recruitment and retention. Relevant MEDLINE articles and clinical studies were reviewed, and the design, implementation, and results of the 2 community-based studies were evaluated. Information from the literature, research results, and sample selection, participation, and attrition experiences were synthesized to determine effective approaches for recruitment and retention. Research funding, design, and implementation; recruitment methods; culturally competent approaches; caring, trusting provider-patient relationships; incentives; follow-up; and factors in the rural environment emerged as important issues influencing recruitment and retention. Recruitment and retention of African Americans in rural diabetes research is a significant challenge, and adequate funding should be sought early in the research process. Culturally competent approaches; caring, trusting relationships; incentives; and follow-up are important concepts in successful recruitment, participation, and retention of African Americans. The lessons learned may be applicable to the more widespread issue of recruitment and retention of rural African Americans in diabetes education programs.
A Study of Retention Trends of International Students at a Southwestern Public University

ERIC Educational Resources Information Center

Wong Davis, Kristina Marie

2012-01-01

Literature on factors contributing to the retention of international students remained limited. The purpose of this study was to examine the factors related to retention of international undergraduate degree seeking students through conducting pairwise correlational analysis to test the relationship between retention and age, gender, country of…
The Relationship between Self-Directed Learning Readiness and Student Retention in Nursing Education

ERIC Educational Resources Information Center

Larmon, Brandy H.

2015-01-01

Retention in higher education, especially nursing education, is a concern for nurse educators. Due to the needs of nurse graduates and practicing nurses, the characteristic of self-directed learning in students is often an educational goal of a rigorous nursing curriculum. Program retention is often impacted by such demands. This study, based upon…
Tertiary structural propensities reveal fundamental sequence/structure relationships.

PubMed

Zheng, Fan; Zhang, Jian; Grigoryan, Gevorg

2015-05-05

Extracting useful generalizations from the continually growing Protein Data Bank (PDB) is of central importance. We hypothesize that the PDB contains valuable quantitative information on the level of local tertiary structural motifs (TERMs). We show that by breaking a protein structure into its constituent TERMs, and querying the PDB to characterize the natural ensemble matching each, we can estimate the compatibility of the structure with a given amino acid sequence through a metric we term "structure score." Considering submissions from recent Critical Assessment of Structure Prediction (CASP) experiments, we found a strong correlation (R = 0.69) between structure score and model accuracy, with poorly predicted regions readily identifiable. This performance exceeds that of leading atomistic statistical energy functions. Furthermore, TERM-based analysis of two prototypical multi-state proteins rapidly produced structural insights fully consistent with prior extensive experimental studies. We thus find that TERM-based analysis should have considerable utility for protein structural biology. Copyright © 2015 Elsevier Ltd. All rights reserved.
Quantitative structure-activity relationships for reactivities of sulfate and hydroxyl radicals with aromatic contaminants through single-electron transfer pathway.

PubMed

Luo, Shuang; Wei, Zongsu; Spinney, Richard; Villamena, Frederick A; Dionysiou, Dionysios D; Chen, Dong; Tang, Chong-Jian; Chai, Liyuan; Xiao, Ruiyang

2018-02-15

Sulfate radical anion (SO 4 •- ) and hydroxyl radical (OH) based advanced oxidation technologies has been extensively used for removal of aromatic contaminants (ACs) in waters. In this study, we investigated the Gibbs free energy (ΔG SET ∘ ) of the single electron transfer (SET) reactions for 76 ACs with SO 4 •- and OH, respectively. The result reveals that SO 4 •- possesses greater propensity to react with ACs through the SET channel than OH. We hypothesized that the electron distribution within the molecule plays an essential role in determining the ΔG SET ∘ and subsequent SET reactions. To test the hypothesis, a quantitative structure-activity relationship (QSAR) model was developed for predicting ΔG SET ∘ using the highest occupied molecular orbital energies (E HOMO ), a measure of electron distribution and donating ability. The standardized QSAR models are reported to be ΔG ° SET =-0.97×E HOMO - 181 and ΔG ° SET =-0.97×E HOMO - 164 for SO 4 •- and OH, respectively. The models were internally and externally validated to ensure robustness and predictability, and the application domain and limitations were discussed. The single-descriptor based models account for 95% of the variability for SO 4 •- and OH. These results provide the mechanistic insight into the SET reaction pathway of radical and non-radical bimolecular reactions, and have important applications for radical based oxidation technologies to remove target ACs in different waters. Copyright © 2017 Elsevier B.V. All rights reserved.
A penalized quantitative structure-property relationship study on melting point of energetic carbocyclic nitroaromatic compounds using adaptive bridge penalty.

PubMed

Al-Fakih, A M; Algamal, Z Y; Lee, M H; Aziz, M

2018-05-01

A penalized quantitative structure-property relationship (QSPR) model with adaptive bridge penalty for predicting the melting points of 92 energetic carbocyclic nitroaromatic compounds is proposed. To ensure the consistency of the descriptor selection of the proposed penalized adaptive bridge (PBridge), we proposed a ridge estimator ([Formula: see text]) as an initial weight in the adaptive bridge penalty. The Bayesian information criterion was applied to ensure the accurate selection of the tuning parameter ([Formula: see text]). The PBridge based model was internally and externally validated based on [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], the Y-randomization test, [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text] and the applicability domain. The validation results indicate that the model is robust and not due to chance correlation. The descriptor selection and prediction performance of PBridge for the training dataset outperforms the other methods used. PBridge shows the highest [Formula: see text] of 0.959, [Formula: see text] of 0.953, [Formula: see text] of 0.949 and [Formula: see text] of 0.959, and the lowest [Formula: see text] and [Formula: see text]. For the test dataset, PBridge shows a higher [Formula: see text] of 0.945 and [Formula: see text] of 0.948, and a lower [Formula: see text] and [Formula: see text], indicating its better prediction performance. The results clearly reveal that the proposed PBridge is useful for constructing reliable and robust QSPRs for predicting melting points prior to synthesizing new organic compounds.
The Relationship between Cranial Structure, Biomechanical Performance and Ecological Diversity in Varanoid Lizards

PubMed Central

McCurry, Matthew R.; Mahony, Michael; Clausen, Phillip D.; Quayle, Michelle R.; Walmsley, Christopher W.; Jessop, Tim S.; Wroe, Stephen; Richards, Heather; McHenry, Colin R.

2015-01-01

Skull structure is intimately associated with feeding ability in vertebrates, both in terms of specific performance measures and general ecological characteristics. This study quantitatively assessed variation in the shape of the cranium and mandible in varanoid lizards, and its relationship to structural performance (von Mises strain) and interspecific differences in feeding ecology. Geometric morphometric and linear morphometric analyses were used to evaluate morphological differences, and finite element analysis was used to quantify variation in structural performance (strain during simulated biting, shaking and pulling). This data was then integrated with ecological classes compiled from relevant scientific literature on each species in order to establish structure-function relationships. Finite element modelling results showed that variation in cranial morphology resulted in large differences in the magnitudes and locations of strain in biting, shaking and pulling load cases. Gracile species such as Varanus salvadorii displayed high strain levels during shaking, especially in the areas between the orbits. All models exhibit less strain during pull back loading compared to shake loading, even though a larger force was applied (pull =30N, shake = 20N). Relationships were identified between the morphology, performance, and ecology. Species that did not feed on hard prey clustered in the gracile region of cranial morphospace and exhibited significantly higher levels of strain during biting (P = 0.0106). Species that fed on large prey clustered in the elongate area of mandible morphospace. This relationship differs from those that have been identified in other taxonomic groups such as crocodiles and mammals. This difference may be due to a combination of the open ‘space-frame’ structure of the varanoid lizard skull, and the ‘pull back’ behaviour that some species use for processing large prey. PMID:26106889
Participant Retention in a Longitudinal National Telephone Survey of African American Men and Women

PubMed Central

Holt, Cheryl L.; Le, Daisy; Calvanelli, Joe; Huang, Jin; Clark, Eddie M.; Roth, David L.; Williams, Beverly; Schulz, Emily

2015-01-01

Objective The purpose of this article is to describe participant demographic factors related to retention, and to report on retention strategies in a national study of African Americans re-contacted 2.5 years after an initial baseline telephone interview. Design & Setting The Religion and Health in African Americans (RHIAA) study was originally developed as a cross-sectional telephone survey to examine relationships between religious involvement and health-related factors in a national sample of African Americans. The cohort was re-contacted on average of 2.5 years later for a follow-up interview. Participants RHIAA participants were 2,803 African American men (1,202) and women (1,601). Interventions RHIAA used retention strategies consistent with recommendations from Hunt and White.1 Participants also received a lay summary of project findings. Main outcome measures Retention at the follow-up interview. Results Retention rates ranged from 39%–41%. Retained participants tended to be older and female. In age- and sex-adjusted analyses, retained participants were more educated, single, and in better health status than those not retained. There was no difference in religious involvement in adjusted analyses. Conclusions Although overall retention rates are lower than comparable longitudinal studies, RHIAA was not originally designed as a longitudinal study and so lacked a number of structures associated with long-term studies. However, this project illustrates the feasibility of conducting lengthy cold call telephone interviews with an African American population and helps to identify some participant factors related to retention and study strategies that may aid in retention. PMID:26118147
Influence of forest structure and experimental green-tree retention on northern flying squirrel (Glaucomys sabrinus) abundance

Treesearch

Gillian L. Holloway; Winston P. Smith; Charles B. Halpern; Robert A. Gitzen; Christine C. Maguire; Stephen D. West

2012-01-01

In many regions of the world, forest management has shifted from practices emphasizing timber production to more sustainable harvesting that integrates ecological values, including maintenance of biodiversity, wildlife habitat, and ecological goods and services. To this end, management strategies emphasize retention of stand structures that meet the needs of forest-...
Predictors of home healthcare nurse retention.

PubMed

Ellenbecker, Carol Hall; Porell, Frank W; Samia, Linda; Byleckie, James J; Milburn, Michael

2008-01-01

To examine the level of job satisfaction and test a theoretical model of the direct and indirect effects of job satisfaction, and individual nurse and agency characteristics, on intent to stay and retention for home healthcare nurses. A descriptive correlation study of home healthcare nurses in six New England states. Home healthcare nurse job satisfaction self-report data was collected with the HHNJS survey questionnaire & Retention Survey Questionnaire. Based on a structural equation model, job tenure and job satisfaction were the strongest predictors of nurse retention. Understanding the variables associated with home healthcare nurse retention can help agencies retain nurses in a time of severe nurse shortages and increased patient demand. Predicted nursing shortages and increasing demand have made the retention of experienced, qualified nursing staff essential to assure access to high-quality home healthcare services in the future.

Relationships between avian richness and landscape structure at multiple scales using multiple landscapes

USGS Publications Warehouse

Mitchell, M.S.; Rutzmoser, S.H.; Wigley, T.B.; Loehle, C.; Gerwin, J.A.; Keyser, P.D.; Lancia, R.A.; Perry, R.W.; Reynolds, C.J.; Thill, R.E.; Weih, R.; White, D.; Wood, P.B.

2006-01-01

Little is known about factors that structure biodiversity on landscape scales, yet current land management protocols, such as forest certification programs, place an increasing emphasis on managing for sustainable biodiversity at landscape scales. We used a replicated landscape study to evaluate relationships between forest structure and avian diversity at both stand and landscape-levels. We used data on bird communities collected under comparable sampling protocols on four managed forests located across the Southeastern US to develop logistic regression models describing relationships between habitat factors and the distribution of overall richness and richness of selected guilds. Landscape models generated for eight of nine guilds showed a strong relationship between richness and both availability and configuration of landscape features. Diversity of topographic features and heterogeneity of forest structure were primary determinants of avian species richness. Forest heterogeneity, in both age and forest type, were strongly and positively associated with overall avian richness and richness for most guilds. Road density was associated positively but weakly with avian richness. Landscape variables dominated all models generated, but no consistent patterns in metrics or scale were evident. Model fit was strong for neotropical migrants and relatively weak for short-distance migrants and resident species. Our models provide a tool that will allow managers to evaluate and demonstrate quantitatively how management practices affect avian diversity on landscapes.
Student Satisfaction and Its Influence on Semester-to-Semester Retention

ERIC Educational Resources Information Center

Servi, Angela M.

2017-01-01

This study examined students' ratings of satisfaction and importance of academic advising and instructional effectiveness in relation to their retention from semester to semester at one two-year technical college. Class levels and age groups were also studied for relationships to retention and student perceptions of satisfaction and importance.…
The Effect of Financial Aid on Community College Student Retention

ERIC Educational Resources Information Center

Brooks, Debbie Carlton

2016-01-01

Community college student success relies on an examination of critical elements affecting the retention of first-year students. This mixed method study examined the effects of financial aid on community college student retention at a large multi-campus college in Charlotte, North Carolina. The study examined the relationship of financial aid…
Student retention in athletic training education programs.

PubMed

Dodge, Thomas M; Mitchell, Murray F; Mensch, James M

2009-01-01

The success of any academic program, including athletic training, depends upon attracting and keeping quality students. The nature of persistent students versus students who prematurely leave the athletic training major is not known. Understanding the profiles of athletic training students who persist or leave is important. To (1) explore the relationships among the following variables: anticipatory factors, academic integration, clinical integration, social integration, and motivation; (2) determine which of the aforementioned variables discriminate between senior athletic training students and major changers; and (3) identify which variable is the strongest predictor of persistence in athletic training education programs. Descriptive study using a qualitative and quantitative mixed-methods approach. Thirteen athletic training education programs located in District 3 of the National Athletic Trainers' Association. Ninety-four senior-level athletic training students and 31 college students who changed majors from athletic training to another degree option. Data were collected with the Athletic Training Education Program Student Retention Questionnaire (ATEPSRQ). Data from the ATEPSRQ were analyzed via Pearson correlations, multivariate analysis of variance, univariate analysis of variance, and a stepwise discriminant analysis. Open-ended questions were transcribed and analyzed using open, axial, and selective coding procedures. Member checks and peer debriefing techniques ensured trustworthiness of the study. Pearson correlations identified moderate relationships among motivation and clinical integration (r = 0.515, P < .01) and motivation and academic integration (r = 0.509, P < .01). Univariate analyses of variance showed that academic integration (F(1,122) = 8.483, P < .004), clinical integration (F(1,119) = 30.214, P < .001), and motivation (F(1,121) = 68.887, P < .001) discriminated between seniors and major changers. Discriminant analysis indicated that
Optimized Delivery System Achieves Enhanced Endomyocardial Stem Cell Retention

PubMed Central

Behfar, Atta; Latere, Jean-Pierre; Bartunek, Jozef; Homsy, Christian; Daro, Dorothee; Crespo-Diaz, Ruben J.; Stalboerger, Paul G.; Steenwinckel, Valerie; Seron, Aymeric; Redfield, Margaret M.; Terzic, Andre

2014-01-01

Background Regenerative cell-based therapies are associated with limited myocardial retention of delivered stem cells. The objective of this study is to develop an endocardial delivery system for enhanced cell retention. Methods and Results Stem cell retention was simulated in silico using one and three-dimensional models of tissue distortion and compliance associated with delivery. Needle designs, predicted to be optimal, were accordingly engineered using nitinol – a nickel and titanium alloy displaying shape memory and super-elasticity. Biocompatibility was tested with human mesenchymal stem cells. Experimental validation was performed with species-matched cells directly delivered into Langendorff-perfused porcine hearts or administered percutaneously into the endocardium of infarcted pigs. Cell retention was quantified by flow cytometry and real time quantitative polymerase chain reaction methodology. Models, computing optimal distribution of distortion calibrated to favor tissue compliance, predicted that a 75°-curved needle featuring small-to-large graded side holes would ensure the highest cell retention profile. In isolated hearts, the nitinol curved needle catheter (C-Cath) design ensured 3-fold superior stem cell retention compared to a standard needle. In the setting of chronic infarction, percutaneous delivery of stem cells with C-Cath yielded a 37.7±7.1% versus 10.0±2.8% retention achieved with a traditional needle, without impact on biocompatibility or safety. Conclusions Modeling guided development of a nitinol-based curved needle delivery system with incremental side holes achieved enhanced myocardial stem cell retention. PMID:24326777
Relationship of magnetic field strength and brightness of fine-structure elements in the solar temperature minimum region

NASA Technical Reports Server (NTRS)

Cook, J. W.; Ewing, J. A.

1990-01-01

A quantitative relationship was determined between magnetic field strength (or magnetic flux) from photospheric magnetograph observations and the brightness temperature of solar fine-structure elements observed at 1600 A, where the predominant flux source is continuum emission from the solar temperature minimum region. A Kitt Peak magnetogram and spectroheliograph observations at 1600 A taken during a sounding rocket flight of the High Resolution Telescope and Spectrograph from December 11, 1987 were used. The statistical distributions of brightness temperature in the quiet sun at 1600 A, and absolute value of magnetic field strength in the same area were determined from these observations. Using a technique which obtains the best-fit relationship of a given functional form between these two histogram distributions, a quantitative relationship was determined between absolute value of magnetic field strength B and brightness temperature which is essentially linear from 10 to 150 G. An interpretation is suggested, in which a basal heating occurs generally, while brighter elements are produced in magnetic regions with temperature enhancements proportional to B.
Quantitative Structure-Activity Relationships for Organophosphate Enzyme Inhibition (Briefing Charts)

DTIC Science & Technology

2011-09-22

OPs) are a group of pesticides that inhibit enzymes such as acetylcholinesterase. Numerous OP structural variants exist and toxicity data can be...and human toxicity studies especially for OPs lacking experimental data. 15. SUBJECT TERMS QSAR Organophosphates...structure and mechanism of toxicity c) Linking QSAR and OP PBPK/PD 2. Methods a) Physiochemical Descriptors b) Regression Techniques 3. Results a
Drug interaction study of flavonoids toward CYP3A4 and their quantitative structure activity relationship (QSAR) analysis for predicting potential effects.

PubMed

Li, Yannan; Ning, Jing; Wang, Yan; Wang, Chao; Sun, Chengpeng; Huo, Xiaokui; Yu, Zhenlong; Feng, Lei; Zhang, Baojing; Tian, Xiangge; Ma, Xiaochi

2018-05-09

The high risk of herb-drug interactions (HDIs) mediated by the herbal medicines and dietary supplements which containing abundant flavonoids had become more and more frequent in our daily life. In our study, the inhibition activities of 44 different structures of flavonoids toward human CYPs were systemically evaluated for the first time. According to our results, a remarkable structure-dependent inhibition behavior toward CYP3A4 was observed in vitro. Some flavonoids such as licoflavone (12) and irilone (30) exhibited the selective inhibition toward CYP3 A4 rather than other major human CYPs. To illustrate the interaction mechanism, the inhibition kinetics of various compounds was further performed. Sophoranone (1), apigenin (10), baicalein (11), 5,4'-dihydroxy-3,6,7,8,3'-pentamethoxyflavone (15), myricetin (23) and kushenol K (38) remarkably inhibited the CYP3 A4-catalyzed bufalin 5'-hydroxylation reaction, with K i values of 2.17 ± 0.29, 6.15 ± 0.39, 9.18 ± 3.40, 2.30 ± 0.36, 5.00 ± 2.77 and 1.35 ± 0.25 μM, respectively. Importantly, compounds 1, 11, 15, 23 and 38 could significantly inhibit the metabolism of some clinical drugs in vitro, and these drug-drug interactions (DDIs) of myricetin (23) or kushenol K (38) with clinical drug diazepam were further verified in human primary hepatocytes, respectively. Finally, a quantitative structure-activity relationship (QSAR) of flavonoids with their inhibitory effects toward CYP3 A4 was established using computational methods. Our findings illustrated the high risk of herb-drug interactions (HDIs) caused by flavonoids and revealed the vital structures requirement of natural flavonoids for the HDIs with clinical drugs eliminated by CYP3 A4. Our research provided the useful guidance to safely and rationally use herbal medicines and dietary supplements containing rich natural flavonoids components. Copyright © 2018 Elsevier B.V. All rights reserved.
Research Analysis on MOOC Course Dropout and Retention Rates

ERIC Educational Resources Information Center

Gomez-Zermeno, Marcela Gerogina; Aleman de La Garza, Lorena

2016-01-01

This research's objective was to identify the terminal efficiency of the Massive Online Open Course "Educational Innovation with Open Resources" offered by a Mexican private university. A quantitative methodology was used, combining descriptive statistics and probabilistic models to analyze the levels of retention, completion, and…
Personality Types as an Indicator of Online Student Success and Retention

ERIC Educational Resources Information Center

Meredith, Ben P.

2011-01-01

With online education courses within public institutions realizing lower than average retention and success rates for students, current retention practices and models are falling woefully short of providing workable, viable answers to keeping students and helping them be successful without lowering academic standards. While a relationship between…
Comparative analysis of predictive models for nongenotoxic hepatocarcinogenicity using both toxicogenomics and quantitative structure-activity relationships.

PubMed

Liu, Zhichao; Kelly, Reagan; Fang, Hong; Ding, Don; Tong, Weida

2011-07-18

The primary testing strategy to identify nongenotoxic carcinogens largely relies on the 2-year rodent bioassay, which is time-consuming and labor-intensive. There is an increasing effort to develop alternative approaches to prioritize the chemicals for, supplement, or even replace the cancer bioassay. In silico approaches based on quantitative structure-activity relationships (QSAR) are rapid and inexpensive and thus have been investigated for such purposes. A slightly more expensive approach based on short-term animal studies with toxicogenomics (TGx) represents another attractive option for this application. Thus, the primary questions are how much better predictive performance using short-term TGx models can be achieved compared to that of QSAR models, and what length of exposure is sufficient for high quality prediction based on TGx. In this study, we developed predictive models for rodent liver carcinogenicity using gene expression data generated from short-term animal models at different time points and QSAR. The study was focused on the prediction of nongenotoxic carcinogenicity since the genotoxic chemicals can be inexpensively removed from further development using various in vitro assays individually or in combination. We identified 62 chemicals whose hepatocarcinogenic potential was available from the National Center for Toxicological Research liver cancer database (NCTRlcdb). The gene expression profiles of liver tissue obtained from rats treated with these chemicals at different time points (1 day, 3 days, and 5 days) are available from the Gene Expression Omnibus (GEO) database. Both TGx and QSAR models were developed on the basis of the same set of chemicals using the same modeling approach, a nearest-centroid method with a minimum redundancy and maximum relevancy-based feature selection with performance assessed using compound-based 5-fold cross-validation. We found that the TGx models outperformed QSAR in every aspect of modeling. For example, the
Quantitative structure activity relationships of some pyridine derivatives as corrosion inhibitors of steel in acidic medium.

PubMed

El Ashry, El Sayed H; El Nemr, Ahmed; Ragab, Safaa

2012-03-01

Quantum chemical calculations using the density functional theory (B3LYP/6-31G DFT) and semi-empirical AM1 methods were performed on ten pyridine derivatives used as corrosion inhibitors for mild steel in acidic medium to determine the relationship between molecular structure and their inhibition efficiencies. Quantum chemical parameters such as total negative charge (TNC) on the molecule, energy of highest occupied molecular orbital (E (HOMO)), energy of lowest unoccupied molecular orbital (E (LUMO)) and dipole moment (μ) as well as linear solvation energy terms, molecular volume (Vi) and dipolar-polarization (π) were correlated to corrosion inhibition efficiency of ten pyridine derivatives. A possible correlation between corrosion inhibition efficiencies and structural properties was searched to reduce the number of compounds to be selected for testing from a library of compounds. It was found that theoretical data support the experimental results. The results were used to predict the corrosion inhibition of 24 related pyridine derivatives.
Consideration of Cosmetic Surgery As Part of Women's Benefit-Provisioning Mate Retention Strategy.

PubMed

Atari, Mohammad; Barbaro, Nicole; Sela, Yael; Shackelford, Todd K; Chegeni, Razieh

2017-01-01

Individuals perform mate retention behaviors to minimize the risk of partner infidelity and relationship dissolution. The current study investigates whether consideration of cosmetic surgery can be conceptualized as part of a broader strategy of mate retention for women, but not men. We hypothesized that women's consideration of cosmetic surgery would be positively associated with performance frequencies of Benefit-Provisioning and Cost-Inflicting mate retention behaviors. We recruited 203 individuals (54% women) in committed heterosexual relationships from Tehran, Iran. Results indicate a positive association between consideration of cosmetic surgery and Benefit-Provisioning mate retention behaviors for women, but not men. There was no association between consideration of cosmetic surgery and Cost-Inflicting mate retention behaviors. Women therefore may consider cosmetic surgery to improve their physical attractiveness as part of a Benefit-Provisioning strategy to retain a long-term mate. We discuss limitations of the study and highlight future directions for research from an evolutionary perspective.
Novel Uses of In Vitro Data to Develop Quantitative Biological Activity Relationship Models for in Vivo Carcinogenicity Prediction.

PubMed

Pradeep, Prachi; Povinelli, Richard J; Merrill, Stephen J; Bozdag, Serdar; Sem, Daniel S

2015-04-01

The availability of large in vitro datasets enables better insight into the mode of action of chemicals and better identification of potential mechanism(s) of toxicity. Several studies have shown that not all in vitro assays can contribute as equal predictors of in vivo carcinogenicity for development of hybrid Quantitative Structure Activity Relationship (QSAR) models. We propose two novel approaches for the use of mechanistically relevant in vitro assay data in the identification of relevant biological descriptors and development of Quantitative Biological Activity Relationship (QBAR) models for carcinogenicity prediction. We demonstrate that in vitro assay data can be used to develop QBAR models for in vivo carcinogenicity prediction via two case studies corroborated with firm scientific rationale. The case studies demonstrate the similarities between QBAR and QSAR modeling in: (i) the selection of relevant descriptors to be used in the machine learning algorithm, and (ii) the development of a computational model that maps chemical or biological descriptors to a toxic endpoint. The results of both the case studies show: (i) improved accuracy and sensitivity which is especially desirable under regulatory requirements, and (ii) overall adherence with the OECD/REACH guidelines. Such mechanism based models can be used along with QSAR models for prediction of mechanistically complex toxic endpoints. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Quantitative structure-activity relationship for the oxidation of aromatic organic contaminants in water by TAML/H2O2.

PubMed

Su, Hanrui; Yu, Chunyang; Zhou, Yongfeng; Gong, Lidong; Li, Qilin; Alvarez, Pedro J J; Long, Mingce

2018-05-02

Tetra-amido macrocyclic ligand (TAML) activator is a functional analog of peroxidase enzymes, which activates hydrogen peroxide (H 2 O 2 ) to form high valence iron-oxo complexes that selectively degrade persistent aromatic organic contaminants (ACs) in water. Here, we develop quantitative structure-activity relationship (QSAR) models based on measured pseudo first-order kinetic rate coefficients (k obs ) of 29 ACs (e.g., phenols and pharmaceuticals) oxidized by TAML/H 2 O 2 at neutral and basic pH values to gain mechanistic insight on the selectivity and pH dependence of TAML/H 2 O 2 systems. These QSAR models infer that electron donating ability (E HOMO ) is the most important AC characteristic for TAML/H 2 O 2 oxidation, pointing to a rate-limiting single-electron transfer (SET) mechanism. Oxidation rates at pH 7 also depend on AC reactive indices such as f min - and qH + , which respectively represent propensity for electrophilic attack and the most positive net atomic charge on hydrogen atoms. At pH 10, TAML/H 2 O 2 is more reactive towards ACs with a lower hydrogen to carbon atoms ratio (#H:C), suggesting the significance of hydrogen atom abstraction. In addition, lnk obs of 14 monosubstituted phenols is negatively correlated with Hammett constants (σ) and exhibits similar sensitivity to substituent effects as horseradish peroxidase. Although accurately predicting degradation rates of specific ACs in complex wastewater matrices could be difficult, these QSAR models are statistically robust and help predict both relative degradability and reaction mechanism for TAML/H 2 O 2 -based treatment processes. Copyright © 2018 Elsevier Ltd. All rights reserved.
Relationship between retention and peer tutoring for at-risk students.

PubMed

Higgins, Bonnie

2004-07-01

Although state governing bodies and community agencies have requested increased enrollment in nursing programs, this would be futile without curtailment of the student attrition rate. This article describes the use of a peer-tutoring program to increase retention of students at risk of failing a medical-surgical nursing course.
From in silica to in silico: retention thermodynamics at solid-liquid interfaces.

PubMed

El Hage, Krystel; Bemish, Raymond J; Meuwly, Markus

2018-06-28

The dynamics of solvated molecules at the solid/liquid interface is essential for a molecular-level understanding for the solution thermodynamics in reversed phase liquid chromatography (RPLC). The heterogeneous nature of the systems and the competing intermolecular interactions makes solute retention in RPLC a surprisingly challenging problem which benefits greatly from modelling at atomistic resolution. However, the quality of the underlying computational model needs to be sufficiently accurate to provide a realistic description of the energetics and dynamics of systems, especially for solution-phase simulations. Here, the retention thermodynamics and the retention mechanism of a range of benzene-derivatives in C18 stationary-phase chains in contact with water/methanol mixtures is studied using point charge (PC) and multipole (MTP) electrostatic models. The results demonstrate that free energy simulations with a faithful MTP representation of the computational model provide quantitative and molecular level insight into the thermodynamics of adsorption/desorption in chromatographic systems while a conventional PC representation fails in doing so. This provides a rational basis to develop more quantitative and validated models for the optimization of separation systems.
Home healthcare nurse retention and patient outcome model: discussion and model development.

PubMed

Ellenbecker, Carol Hall; Cushman, Margaret

2012-08-01

This paper discusses additions to an empirically tested model of home healthcare nurse retention. An argument is made that the variables of shared decision-making and organizational commitment be added to the model based on the authors' previous research and additional evidence from the literature. Previous research testing the home healthcare nurse retention model established empirical relationships between nurse, agency, and area characteristics to nurse job satisfaction, intent to stay, and retention. Unexplained model variance prompted a new literature search to augment understanding of nurse retention and patient and agency outcomes. Data come from the authors' previous research, and a literature search from 1990 to 2011 on the topics organizational commitment, shared decision-making, nurse retention, patient outcomes and agency performance. The literature provides a rationale for the additional variables of shared decision-making and affective and continuous organizational commitment, linking these variables to nurse job satisfaction, nurse intent to stay, nurse retention and patient outcomes and agency performance. Implications for nursing. The new variables in the model suggest that all agencies, even those not struggling to retain nurses, should develop interventions to enhance nurse job satisfaction to assure quality patient outcomes. The new nurse retention and patient outcome model increases our understanding of nurse retention. An understanding of the relationship among these variables will guide future research and the development of interventions to create and maintain nursing work environments that contribute to nurse affective agency commitment, nurse retention and quality of patient outcomes. © 2011 Blackwell Publishing Ltd.
Relationship among visual field, blood flow, and neural structure measurements in glaucoma.

PubMed

Hwang, John C; Konduru, Ranjith; Zhang, Xinbo; Tan, Ou; Francis, Brian A; Varma, Rohit; Sehi, Mitra; Greenfield, David S; Sadda, Srinivas R; Huang, David

2012-05-17

To determine the relationship among visual field, neural structural, and blood flow measurements in glaucoma. Case-control study. Forty-seven eyes of 42 patients with perimetric glaucoma were age-matched with 27 normal eyes of 27 patients. All patients underwent Doppler Fourier-domain optical coherence tomography to measure retinal blood flow and standard glaucoma evaluation with visual field testing and quantitative structural imaging. Linear regression analysis was performed to analyze the relationship among visual field, blood flow, and structure, after all variables were converted to logarithmic decibel scale. Retinal blood flow was reduced in glaucoma eyes compared to normal eyes (P < 0.001). Visual field loss was correlated with both reduced retinal blood flow and structural loss of rim area and retinal nerve fiber layer (RNFL). There was no correlation or paradoxical correlation between blood flow and structure. Multivariate regression analysis revealed that reduced blood flow and structural loss are independent predictors of visual field loss. Each dB decrease in blood flow was associated with at least 1.62 dB loss in mean deviation (P ≤ 0.001), whereas each dB decrease in rim area and RNFL was associated with 1.15 dB and 2.56 dB loss in mean deviation, respectively (P ≤ 0.03). There is a close link between reduced retinal blood flow and visual field loss in glaucoma that is largely independent of structural loss. Further studies are needed to elucidate the causes of the vascular dysfunction and potential avenues for therapeutic intervention. Blood flow measurement may be useful as an independent assessment of glaucoma severity.
A Comparative Trend Analysis of Institutional Variables and Retention Rates in Publicly Funded Institutions

ERIC Educational Resources Information Center

Lenhardt, Jenna L.

2017-01-01

This study focused on student retention trends in institutional spending and student retention rates. The research also investigated the relationship between student retention and the student-to-faculty ratio. The sample was comprised of 14 publicly funded higher education institutions that had an M1Carnegie classification and were located in one…

Imidazole derivatives as angiotensin II AT1 receptor blockers: Benchmarks, drug-like calculations and quantitative structure-activity relationships modeling

NASA Astrophysics Data System (ADS)

Alloui, Mebarka; Belaidi, Salah; Othmani, Hasna; Jaidane, Nejm-Eddine; Hochlaf, Majdi

2018-03-01

We performed benchmark studies on the molecular geometry, electron properties and vibrational analysis of imidazole using semi-empirical, density functional theory and post Hartree-Fock methods. These studies validated the use of AM1 for the treatment of larger systems. Then, we treated the structural, physical and chemical relationships for a series of imidazole derivatives acting as angiotensin II AT1 receptor blockers using AM1. QSAR studies were done for these imidazole derivatives using a combination of various physicochemical descriptors. A multiple linear regression procedure was used to design the relationships between molecular descriptor and the activity of imidazole derivatives. Results validate the derived QSAR model.
A Quantitative Exploration of the Relationship between Patient Health and Electronic Personal Health Records

ERIC Educational Resources Information Center

Hines, Denise Williams

2009-01-01

The use of electronic personal health records is becoming increasingly more popular as healthcare providers, healthcare and government leaders, and patients are seeking ways to improve healthcare quality and to decrease costs (Abrahamsen, 2007). This quantitative, descriptive correlational study examined the relationship between the degree of…
A Quantitative review of relationships between Ecosystem services

NASA Astrophysics Data System (ADS)

Lee, H.; Lautenbach, S.

2014-12-01

Each decision in natural resources management can generate trade-offs with respect to the provisioning of ecosystem services (ES). If the increase of one ES happens directly or indirectly at the cost of another ES, an attempt to maximize the provision of a single ES will lead to suboptimal results. However, decisions in natural resources management are often made without considering such trade-offs, despite their crucial role toward supporting better decision-making. The research on trade-offs between ES has gained some attention in the scientific community. However, a synthesis on existing knowledge and knowledge gaps is missing so far. We aim at closing that gap by a quantitative review of recent literature on trade-offs of ES. We looked at the pairs of ES that have been studied in ~100 case studies that report on trade-offs between ES. If a case study analyzed more than one ES pair, we looked at all pairwise combinations. We categorized relationships between these pairs of ES into the categories "trade-off", "synergy" or "no-effect". Most pairs of ES had a clear association with one category: the majority of case studies that studied a specific pair of ES identified the same category of relationship between the two ES. Pairs of regulating services were typically synergetic in relationship, whereas provisioning services and regulating services typically showed a trade-off. However, for several pairs of ES we were not able to identify a dominate category of relationship. Our hypothesis is that this relates to either the scale of the analysis, the land system where the analysis took place or the method used to quantify the relationship. The number of case studies for each pair of ES was spread unevenly. This hinders the support for a conclusive statement drawn for the pairs. Our results showed further that the method used to identify the relationship between services had a strong effect on the direction of the effect. This suggests that researchers should consider
Structure-Thermodynamics-Antioxidant Activity Relationships of Selected Natural Phenolic Acids and Derivatives: An Experimental and Theoretical Evaluation

PubMed Central

Zheng, Jie; Liang, Guizhao

2015-01-01

Phenolic acids and derivatives have potential biological functions, however, little is known about the structure-activity relationships and the underlying action mechanisms of these phenolic acids to date. Herein we investigate the structure-thermodynamics-antioxidant relationships of 20 natural phenolic acids and derivatives using DPPH• scavenging assay, density functional theory calculations at the B3LYP/6-311++G(d,p) levels of theory, and quantitative structure-activity relationship (QSAR) modeling. Three main working mechanisms (HAT, SETPT and SPLET) are explored in four micro-environments (gas-phase, benzene, water and ethanol). Computed thermodynamics parameters (BDE, IP, PDE, PA and ETE) are compared with the experimental radical scavenging activities against DPPH•. Available theoretical and experimental investigations have demonstrated that the extended delocalization and intra-molecular hydrogen bonds are the two main contributions to the stability of the radicals. The C = O or C = C in COOH, COOR, C = CCOOH and C = CCOOR groups, and orthodiphenolic functionalities are shown to favorably stabilize the specific radical species to enhance the radical scavenging activities, while the presence of the single OH in the ortho position of the COOH group disfavors the activities. HAT is the thermodynamically preferred mechanism in the gas phase and benzene, whereas SPLET in water and ethanol. Furthermore, our QSAR models robustly represent the structure-activity relationships of these explored compounds in polar media. PMID:25803685
Structure-thermodynamics-antioxidant activity relationships of selected natural phenolic acids and derivatives: an experimental and theoretical evaluation.

PubMed

Chen, Yuzhen; Xiao, Huizhi; Zheng, Jie; Liang, Guizhao

2015-01-01

Phenolic acids and derivatives have potential biological functions, however, little is known about the structure-activity relationships and the underlying action mechanisms of these phenolic acids to date. Herein we investigate the structure-thermodynamics-antioxidant relationships of 20 natural phenolic acids and derivatives using DPPH• scavenging assay, density functional theory calculations at the B3LYP/6-311++G(d,p) levels of theory, and quantitative structure-activity relationship (QSAR) modeling. Three main working mechanisms (HAT, SETPT and SPLET) are explored in four micro-environments (gas-phase, benzene, water and ethanol). Computed thermodynamics parameters (BDE, IP, PDE, PA and ETE) are compared with the experimental radical scavenging activities against DPPH•. Available theoretical and experimental investigations have demonstrated that the extended delocalization and intra-molecular hydrogen bonds are the two main contributions to the stability of the radicals. The C = O or C = C in COOH, COOR, C = CCOOH and C = CCOOR groups, and orthodiphenolic functionalities are shown to favorably stabilize the specific radical species to enhance the radical scavenging activities, while the presence of the single OH in the ortho position of the COOH group disfavors the activities. HAT is the thermodynamically preferred mechanism in the gas phase and benzene, whereas SPLET in water and ethanol. Furthermore, our QSAR models robustly represent the structure-activity relationships of these explored compounds in polar media.
Predictors of Calcium Retention in Adolescent Boys

PubMed Central

Hill, Kathleen M.; Braun, Michelle; Kern, Mark; Martin, Berdine R.; Navalta, James W.; Sedlock, Darlene A.; McCabe, Linda; McCabe, George P.; Peacock, Munro; Weaver, Connie M.

2008-01-01

Context: The relationship between calcium (Ca) intake and Ca retention in adolescent boys was recently reported. Objective: This study evaluated the influence of Ca intake, serum hormone levels, biomarkers of bone metabolism, habitual physical activity, habitual Ca intake, and physical fitness on Ca retention in the same sample. Design: This study was a randomized, cross-over design that consisted of two 3-wk metabolic balance periods. Setting: The study took place on a university campus as a summer camp. Patients or Other Participants: A total of 31 American white boys (13–15 yr) participated in the study. Interventions: Each subject consumed a controlled diet with one of five high-low Ca intake pairs that ranged from 670-2003 mg/d, which was manipulated utilizing a fortified beverage. Main Outcome Measures: Ca retention was determined by Ca intake minus urinary and fecal Ca excretion during each balance period. Results: Ca intake explained 21.7% of the variability in Ca retention, and serum IGF-I concentration explained an additional 11.5%. Other serum hormone levels did not significantly add to the model. Biomarkers of bone metabolism, habitual physical activity, habitual Ca intake, and physical fitness were not significant predictors of Ca retention in adolescent boys. Conclusions: IGF-I, a regulator of growth during puberty, is an important predictor of Ca retention in adolescent boys. However, dietary Ca intake is an even greater predictor of Ca retention during this period of growth. PMID:18840643
Use of the ciliated protozoan Tetrahymena pyriformis for the assessment of toxicity and quantitative structure--activity relationships of xenobiotics: comparison with the Microtox test.

PubMed

Bogaerts, P; Bohatier, J; Bonnemoy, F

2001-07-01

Cytotoxicity and quantitative structure-activity relationships of 13 inorganic and 21 organic substances were determined using three bioassays performed on the ciliated protozoan Tetrahymena pyriformis and the luminescent bacterium Vibrio fischeri. The best concordance of toxicity results was observed between the T. pyriformis FDA--esterase activity and population growth inhibition tests for the organic compounds. The sensitivity of these two assays is compared with that of the Microtox test. The T. pyriformis FDA test showed a high sensitivity is most cases. The aim of the current research was to determine whether the relative toxicity of metal ions and organic molecules, with these three bioassays, was predictable using three ion characteristics and hydrophobicity, respectively. For metal ions, the variable that best modeled the toxicity data obtained with the two T. pyriformis tests was the softness index [sigma(p), i.e., (coordinate bond energy of the metal fluoride--coordinate bond energy of the metal iodide)/(coordinate bond energy of the metal fluoride)]. No correlation was found with the Microtox test. For organic compounds, a significant correlation was observed between the hydrophobicity coefficient and the toxicity data. This correlation is closer with the two tests using Tetrahymena. Copyright 2001 Academic Press.
EFFECTS OF SPATIAL EXTENT ON LANDSCAPE STRUCTURE AND SEDIMENT METAL CONCENTRATION RELATIONSHIPS IN SMALL ESTUARINE SYSTEMS OF THE US MID-ATLANTIC COAST

EPA Science Inventory

Prior studies exploring the quantitative relationship between landscape structure metrics and the ecological condition of receiving waters have used a variety of sampling units (e.g. a watershed, or a buffer around a sampling station) at a variety of spatial scales to generate la...
Evaluation of recruitment and retention strategies for health workers in rural Zambia.

PubMed

Goma, Fastone M; Tomblin Murphy, Gail; MacKenzie, Adrian; Libetwa, Miriam; Nzala, Selestine H; Mbwili-Muleya, Clara; Rigby, Janet; Gough, Amy

2014-01-01

In response to Zambia's critical human resources for health challenges, a number of strategies have been implemented to recruit and retain health workers in rural and remote areas. Prior to this study, the effectiveness of these strategies had not been investigated. The purpose of this study was to determine the impacts of the various health worker retention strategies on health workers in two rural districts of Zambia. Using a modified outcome mapping approach, cross-sectional qualitative and quantitative data were collected from health workers and other stakeholders through focus group discussions and individual interview questionnaires and were supplemented by administrative data. Key themes emerging from qualitative data were identified from transcripts using thematic analysis. Quantitative data were analyzed descriptively as well as by regression modelling. In the latter, the degree to which variation in health workers' self-reported job satisfaction, likelihood of leaving, and frequency of considering leaving, were modelled as functions of participation in each of several retention strategies while controlling for age, gender, profession, and district. Nineteen health worker recruitment and retention strategies were identified and 45 health care workers interviewed in the two districts; participation in each strategy varied from 0% to 80% of study participants. Although a salary top-up for health workers in rural areas was identified as the most effective incentive, almost none of the recruitment and retention strategies were significant predictors of health workers' job satisfaction, likelihood of leaving, or frequency of considering leaving, which were in large part explained by individual characteristics such as age, gender, and profession. These quantitative findings were consistent with the qualitative data, which indicated that existing strategies fail to address major problems identified by health workers in these districts, such as poor living and
Comparison of 3D quantitative structure-activity relationship methods: Analysis of the in vitro antimalarial activity of 154 artemisinin analogues by hypothetical active-site lattice and comparative molecular field analysis

NASA Astrophysics Data System (ADS)

Woolfrey, John R.; Avery, Mitchell A.; Doweyko, Arthur M.

1998-03-01

Two three-dimensional quantitative structure-activity relationship (3D-QSAR) methods, comparative molecular field analysis (CoMFA) and hypothetical active site lattice (HASL), were compared with respect to the analysis of a training set of 154 artemisinin analogues. Five models were created, including a complete HASL and two trimmed versions, as well as two CoMFA models (leave-one-out standard CoMFA and the guided-region selection protocol). Similar r2 and q2 values were obtained by each method, although some striking differences existed between CoMFA contour maps and the HASL output. Each of the four predictive models exhibited a similar ability to predict the activity of a test set of 23 artemisinin analogues, although some differences were noted as to which compounds were described well by either model.
An Investigation of the Factors That Motivate K-12 Christian School Teachers to Participate in Professional Development and the Relationship to Job Satisfaction and Retention

ERIC Educational Resources Information Center

Bailey, Bonita Wingfield

2013-01-01

This study was conducted to advance knowledge by examining the reasons that motivate teachers to participate in professional development and the relationship to teacher job satisfaction and retention in Christian-based K-12 Association of Christian Schools International (ACSI) member schools. The study contributes to the literature in the field…
Postpartum weight retention risk factors and relationship to obesity at 1 year.

PubMed

Endres, Loraine K; Straub, Heather; McKinney, Chelsea; Plunkett, Beth; Minkovitz, Cynthia S; Schetter, Chris D; Ramey, Sharon; Wang, Chi; Hobel, Calvin; Raju, Tonse; Shalowitz, Madeleine U

2015-01-01

To explore risk factors for postpartum weight retention at 1 year after delivery in predominantly low-income women. Data were collected from 774 women with complete height and weight information from participants in the Eunice Kennedy Shriver National Institute of Child Health and Human Development Community Child Health Network, a national five-site, prospective cohort study. Participants were enrolled primarily in the hospitals immediately after delivery. Maternal interviews conducted at 1, 6, and 12 months postpartum identified risk factors for weight retention and included direct measurement of height and weight at 6 and 12 months. Logistic regression assessed the independent contribution of postpartum weight retention on obesity. Women had a mean prepregnancy weight of 161.5 lbs (body mass index [BMI] 27.7). Women gained a mean of 32 lbs while pregnant and had a 1-year mean postpartum weight of 172.6 lbs (BMI 29.4). Approximately 75% of women were heavier 1 year postpartum than they were prepregnancy, including 47.4% retaining more than 10 lbs and 24.2% more than 20 lbs. Women retaining at least 20 lbs were more often African American, younger, poor, less educated, or on pubic insurance. Race and socioeconomic disparities were associated with high prepregnancy BMI and excessive weight gain during pregnancy, associations that were attenuated by breastfeeding at 6 months and moderate exercise. Of the 39.8 with normal prepregnancy BMI, one third became overweight or obese 1 year postpartum. Postpartum weight retention is a significant contributor to the risk for obesity 1 year postpartum, including for women of normal weight prepregnancy. Postpartum, potentially modifiable behaviors may lower the risk. III.
Consideration of Cosmetic Surgery As Part of Women’s Benefit-Provisioning Mate Retention Strategy

PubMed Central

Atari, Mohammad; Barbaro, Nicole; Sela, Yael; Shackelford, Todd K.; Chegeni, Razieh

2017-01-01

Individuals perform mate retention behaviors to minimize the risk of partner infidelity and relationship dissolution. The current study investigates whether consideration of cosmetic surgery can be conceptualized as part of a broader strategy of mate retention for women, but not men. We hypothesized that women’s consideration of cosmetic surgery would be positively associated with performance frequencies of Benefit-Provisioning and Cost-Inflicting mate retention behaviors. We recruited 203 individuals (54% women) in committed heterosexual relationships from Tehran, Iran. Results indicate a positive association between consideration of cosmetic surgery and Benefit-Provisioning mate retention behaviors for women, but not men. There was no association between consideration of cosmetic surgery and Cost-Inflicting mate retention behaviors. Women therefore may consider cosmetic surgery to improve their physical attractiveness as part of a Benefit-Provisioning strategy to retain a long-term mate. We discuss limitations of the study and highlight future directions for research from an evolutionary perspective. PMID:28855884
Universal structural parameter to quantitatively predict metallic glass properties

DOE PAGES

Ding, Jun; Cheng, Yong-Qiang; Sheng, Howard; ...

2016-12-12

Quantitatively correlating the amorphous structure in metallic glasses (MGs) with their physical properties has been a long-sought goal. Here we introduce flexibility volume' as a universal indicator, to bridge the structural state the MG is in with its properties, on both atomic and macroscopic levels. The flexibility volume combines static atomic volume with dynamics information via atomic vibrations that probe local configurational space and interaction between neighbouring atoms. We demonstrate that flexibility volume is a physically appropriate parameter that can quantitatively predict the shear modulus, which is at the heart of many key properties of MGs. Moreover, the new parametermore » correlates strongly with atomic packing topology, and also with the activation energy for thermally activated relaxation and the propensity for stress-driven shear transformations. These correlations are expected to be robust across a very wide range of MG compositions, processing conditions and length scales.« less
Acquisition system environmental effects study. [for capillary-screen propellant retention devices

NASA Technical Reports Server (NTRS)

1975-01-01

The effects of vibration, warm gas exposure, and feed system startup/shutdown fluid dynamics on capillary-screen propellant retention capabilities are quantified. The existing technology is extended to the point where quantitative conlusions in terms of design criteria may be drawn.
Trend of change in retentive force for bar attachments with different materials.

PubMed

Saito, Marie; Kanazawa, Manabu; Takahashi, Hidekazu; Uo, Motohiro; Minakuchi, Shunsuke

2014-12-01

Attachment wear can decrease the retentive force of 2-implant overdentures (2-IODs). The purpose of this in vitro study was to investigate the trend of change in retentive force for 6 different bar attachments during dislodgement. Round and Dolder bars were made of platinum-added gold alloy (PGA), cobalt chromium alloy (Co-Cr), and commercially pure titanium grade IV (Ti). Clips were made of PGA. Retentive force was measured during 7200 dislodging cycles. Simple linear regression analysis was performed in order to investigate the relationship between number of cycles and retentive force (P<.05). Subsequently, wear debris was analyzed, and the surface of the attachments was observed. The retentive force of the Co-Cr round bar attachment (CoCr-R) increased from 57.5 N to 68.3 N and the Ti round bar attachment (Ti-R) from 54.8 N to 59.7 N. However, the retentive force of the PGA round bar attachment (PGA-R) decreased from 69.3 N to 64.0 N. A positive relationship was found between the number of cycles and the retentive force of both CoCr-R and Ti-R. The composition of the wear debris was almost the same as for PGA. For the Dolder bar attachment, no changes were seen in retentive force (between 7.0 N to 12.0 N). For the round bar attachment, the PGA clip and PGA bar showed wear. The retentive force of PGA-R slightly decreased. The retentive force of CoCr-R and Ti-R tended to increase. For the Dolder bar attachment, all 3 types of bar attachment showed no wear. Copyright © 2014 Editorial Council for the Journal of Prosthetic Dentistry. Published by Elsevier Inc. All rights reserved.
College Students Who Are Parents Need Equitable Services for Retention

ERIC Educational Resources Information Center

Lovell, Elyse D'nn

2014-01-01

Growing populations which represent undergraduate students who are parents include females, non-traditional age students, and mothers who are single and living in poverty. Student-parent retention services appeared extremely disproportionate to the number of student-parents on campuses. Student parents in this quantitative analysis showed…
Multivariate analysis of chromatographic retention data as a supplementary means for grouping structurally related compounds.

PubMed

Fasoula, S; Zisi, Ch; Sampsonidis, I; Virgiliou, Ch; Theodoridis, G; Gika, H; Nikitas, P; Pappa-Louisi, A

2015-03-27

In the present study a series of 45 metabolite standards belonging to four chemically similar metabolite classes (sugars, amino acids, nucleosides and nucleobases, and amines) was subjected to LC analysis on three HILIC columns under 21 different gradient conditions with the aim to explore whether the retention properties of these analytes are determined from the chemical group they belong. Two multivariate techniques, principal component analysis (PCA) and discriminant analysis (DA), were used for statistical evaluation of the chromatographic data and extraction similarities between chemically related compounds. The total variance explained by the first two principal components of PCA was found to be about 98%, whereas both statistical analyses indicated that all analytes are successfully grouped in four clusters of chemical structure based on the retention obtained in four or at least three chromatographic runs, which, however should be performed on two different HILIC columns. Moreover, leave-one-out cross-validation of the above retention data set showed that the chemical group in which an analyte belongs can be 95.6% correctly predicted when the analyte is subjected to LC analysis under the same four or three experimental conditions as the all set of analytes was run beforehand. That, in turn, may assist with disambiguation of analyte identification in complex biological extracts. Copyright © 2015 Elsevier B.V. All rights reserved.
Academic Support as a Predictor of Retention to Graduation: New Insights on the Role of Tutoring, Learning Assistance, and Supplemental Instruction

ERIC Educational Resources Information Center

Grillo, Michael C.; Leist, Cathy W.

2013-01-01

This study seeks to examine the relationship between the long-term use of academic support services such as tutoring, learning assistance, and supplemental instruction and retention to graduation. Little research has been devoted to the relationship between academic support and retention to graduation in both the literatures on retention and…
Engagement and Retention in Outpatient Alcoholism Treatment for Women

PubMed Central

Graff, Fiona S.; Morgan, Thomas J.; Epstein, Elizabeth E.; McCrady, Barbara S.; Cook, Sharon M.; Jensen, Noelle K.; Kelly, Shalonda

2011-01-01

Reviews of the dropout literature note significant attrition from addiction treatment. However, consistent predictors have not been identified and few studies have examined factors related to retention and engagement for women in gender-specific treatment. The current study consisted of 102 women and their partners randomized to individual or couples outpatient alcoholism treatment. Women attended more treatment sessions if they were assigned to individual treatment, older, had fewer symptoms of alcohol dependence, had more satisfying marital relationships, had spouses who drank, and had matched preference for treatment condition. Women were more engaged in treatment (i.e., completed more assigned homework) if they had fewer children at home, fewer alcohol dependence symptoms, later age of onset of alcohol diagnosis, more satisfying marital relationships, and spouses who accepted or encouraged their drinking. Results highlight important associations of treatment and relationship variables with treatment retention and engagement. PMID:19444731

Preparing Tomorrow's Administrators: A Quantitative Correlation Study of the Relationship between Emotional Intelligence and Effective Leadership Practices

ERIC Educational Resources Information Center

May-Vollmar, Kelly

2017-01-01

Purpose: The purpose of this quantitative correlation study was to identify whether there is a relationship between emotional intelligence and effective leadership practices, specifically with school administrators in Southern California K-12 public schools. Methods: This study was conducted using a quantitative descriptive design, correlation…
Observations on the relationship of structure to the mechanical properties of thin TD-NiCr sheet

NASA Technical Reports Server (NTRS)

Whittenberger, J. D.

1976-01-01

A study of the relationship between structure and mechanical properties of thin TD-NiCr sheet indicated that the elevated temperature tensile, stress-rupture, and creep strength properties are dependent on grain aspect ratio and sheet thickness. In general, the strength properties increase with increasing grain aspect ratio and sheet thickness. Tensile testing revealed an absence of ductility at elevated temperatures (not less than 1144 K). Significant creep damage as determined by subsequent tensile testing at room temperature occurs after very small amounts (less than 0.1%) of prior creep deformation over the temperature range 1144-1477 K. A threshold stress for creep appears to exist. Creep exposure below the threshold stress at T not less than 1366 K results in almost full retention of room temperature tensile properties.
Cytotoxic lanostane-type triterpenoids from the fruiting bodies of Ganoderma lucidum and their structure-activity relationships.

PubMed

Chen, Shaodan; Li, Xiangmin; Yong, Tianqiao; Wang, Zhanggen; Su, Jiyan; Jiao, Chunwei; Xie, Yizhen; Yang, Burton B

2017-02-07

We conducted a study of Ganoderma lucidum metabolites and isolated 35 lanostane-type triterpenoids, including 5 new ganoderols (1-5). By spectroscopy, we compared the structures of these compounds with known related compounds in this group. All of the isolated compounds were assayed for their effect against the human breast carcinoma cell line MDA-MB-231 and hepatocellular carcinoma cell line HepG2. Corresponding three-dimensional quantitative structure-activity relationship (3D-QSAR) models were built and analyzed using Discovery Studio. These results provide further evidence for anti-cancer constituents within Ganoderma lucidum, and may provide a theoretical foundation for designing novel therapeutic compounds.
Student Retention in Athletic Training Education Programs

PubMed Central

Dodge, Thomas M; Mitchell, Murray F; Mensch, James M

2009-01-01

Context: The success of any academic program, including athletic training, depends upon attracting and keeping quality students. The nature of persistent students versus students who prematurely leave the athletic training major is not known. Understanding the profiles of athletic training students who persist or leave is important. Objective: To (1) explore the relationships among the following variables: anticipatory factors, academic integration, clinical integration, social integration, and motivation; (2) determine which of the aforementioned variables discriminate between senior athletic training students and major changers; and (3) identify which variable is the strongest predictor of persistence in athletic training education programs. Design: Descriptive study using a qualitative and quantitative mixed-methods approach. Setting: Thirteen athletic training education programs located in District 3 of the National Athletic Trainers' Association. Patients or Other Participants: Ninety-four senior-level athletic training students and 31 college students who changed majors from athletic training to another degree option. Data Collection: Data were collected with the Athletic Training Education Program Student Retention Questionnaire (ATEPSRQ). Analysis: Data from the ATEPSRQ were analyzed via Pearson correlations, multivariate analysis of variance, univariate analysis of variance, and a stepwise discriminant analysis. Open-ended questions were transcribed and analyzed using open, axial, and selective coding procedures. Member checks and peer debriefing techniques ensured trustworthiness of the study. Results: Pearson correlations identified moderate relationships among motivation and clinical integration (r = 0.515, P < .01) and motivation and academic integration (r = 0.509, P < .01). Univariate analyses of variance showed that academic integration (F1,122 = 8.483, P < .004), clinical integration (F1,119 = 30.214, P < .001), and
Best Practices in Doctoral Retention: Mentoring

ERIC Educational Resources Information Center

Brill, Judie L.; Balcanoff, Karen K.; Land, Denise; Gogarty, Maurice; Turner, Freda

2014-01-01

The aim of this critical literature review is to outline best practices in doctoral retention and the successful approach of one university to improve graduation success by providing effective mentorship for faculty and students alike. The focus of this literature review is on distance learning relationships between faculty and doctoral students,…
Verbal Abilities as Predictors of Retention among Adolescents in a Therapeutic Community

ERIC Educational Resources Information Center

Wilson, Jeffrey J.; Levin, Frances R.; Donovan, Stephen J.; Nunes, Edward V.

2006-01-01

The relationship between verbal skills and retention among adolescents in substance abuse treatment is understudied. In order to assess verbal predictors of retention, twenty-eight 16-19 year old adolescents in a therapeutic community for substance abuse were evaluated between 30 and 90 days after admission. These adolescents were then followed…
Reproducibility of Quantitative Structural and Physiological MRI Measurements

DTIC Science & Technology

2017-08-09

per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and...Journal Article 3. DATES COVERED (From – To) January 2015 – July 2017 4. TITLE AND SUBTITLE Reproducibility of Quantitative Structural and...NUMBER 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) USAF School of Aerospace Medicine Aeromedical Research Dept/FHOH 2510 Fifth St., Bldg
Quantitative Restoration of the Evolution of Mantle Structures Using Data Assimilation

NASA Astrophysics Data System (ADS)

Ismail-Zadeh, A.; Schubert, G.; Tsepelev, I.

2008-12-01

Rapid progress in imaging deep Earth structures and in studies of physical and chemical properties of mantle rocks facilitates research in assimilation of data related to mantle dynamics. We present a quantitative approach to assimilation of geophysical and geodetic data, which allows for incorporating observations and unknown initial conditions for mantle temperature and flow into a three-dimensional dynamic model in order to determine the initial conditions in the geological past. Once the conditions are determined the evolution of mantle structures can be restore backward in time. We apply data assimilation techniques to model the evolution of mantle plumes and lithospheric slabs. We show that the geometry of the mantle structures changes with time diminishing the degree of surface curvature of the structures, because the heat conduction smoothes the complex thermal surfaces of mantle bodies with time. Present seismic tomography images of mantle structures do not allow definition of the sharp shapes of these structures. Assimilation of mantle temperature and flow to the geological past instead provides a quantitative tool to restore thermal shapes of prominent structures in the past from their diffusive shapes at present.
Studies on the retention mechanism of solutes in hydrophilic interaction chromatography using stoichiometric displacement theory I. The linear relationship of lgk' vs. lg[H2O].

PubMed

Wang, Fei; Yang, Fan; Tian, Yang; Liu, Jiawei; Shen, Jiwei; Bai, Quan

2018-01-01

A stoichiometric displacement model for retention (SDM-R) of small solutes and proteins based on hydrophilic interaction chromatography (HILIC) was presented. A linear equation that related the logarithm of the capacity factor of the solute to the logarithm of the concentration of water in the mobile phase was derived. The stoichiometric displacement parameters, Z (the number of water molecules required to displace a solute from ligands) and lgI (containing a number of constants that relate to the affinity of solute to the ligands) could be obtained from the slope and the intercept of the linear plots of lgk' vs. lg[H 2 O]. The retention behaviors and retention mechanism of 15 kinds of small solutes and 6 kinds of proteins on 5 kinds HILIC columns with different ligands were investigated with SDM-R in typical range of water concentration in mobile phase. A good linear relationship between lgk' and lg[H 2 O] demonstrated that the most rational retention mechanism of solute in HILIC was a stoichiometric displacement process between solute and solvent molecules with water as displacing agents, which was not only valid for small solutes, but also could be used to explain the retention mechanism of biopolymers in HILIC. Comparing with the partition and adsorption models in HILIC, SDM-R was superior to them. Copyright © 2017 Elsevier B.V. All rights reserved.
[Validation of a Japanese version of the Experience in Close Relationship- Relationship Structure].

PubMed

Komura, Kentaro; Murakami, Tatsuya; Toda, Koji

2016-08-01

The purpose of this study was to translate the Experience of Close Relationship-Relationship Structure (ECRRS) and evaluate its validity. In study 1 (N = 982), evidence based internal structure (factor structure, internal consistency, and correlation among sub-scales) and evidence based relations to other variables (depression, reassurance seeking and self-esteem) were confirmed. In study 2 (N = 563), evidence based on internal structure was reconfirmed, and evidence based relations to other variables (IWMS, RQ, and ECR-GO) were confirmed. In study 3 (N = 342), evidence based internal structure (test-retest reliability) was confirmed. Based on these results, we concluded that ECR-RS was valid for measuring adult attachment style.
Learning the Structure of Biomedical Relationships from Unstructured Text

PubMed Central

Percha, Bethany; Altman, Russ B.

2015-01-01

The published biomedical research literature encompasses most of our understanding of how drugs interact with gene products to produce physiological responses (phenotypes). Unfortunately, this information is distributed throughout the unstructured text of over 23 million articles. The creation of structured resources that catalog the relationships between drugs and genes would accelerate the translation of basic molecular knowledge into discoveries of genomic biomarkers for drug response and prediction of unexpected drug-drug interactions. Extracting these relationships from natural language sentences on such a large scale, however, requires text mining algorithms that can recognize when different-looking statements are expressing similar ideas. Here we describe a novel algorithm, Ensemble Biclustering for Classification (EBC), that learns the structure of biomedical relationships automatically from text, overcoming differences in word choice and sentence structure. We validate EBC's performance against manually-curated sets of (1) pharmacogenomic relationships from PharmGKB and (2) drug-target relationships from DrugBank, and use it to discover new drug-gene relationships for both knowledge bases. We then apply EBC to map the complete universe of drug-gene relationships based on their descriptions in Medline, revealing unexpected structure that challenges current notions about how these relationships are expressed in text. For instance, we learn that newer experimental findings are described in consistently different ways than established knowledge, and that seemingly pure classes of relationships can exhibit interesting chimeric structure. The EBC algorithm is flexible and adaptable to a wide range of problems in biomedical text mining. PMID:26219079
Examining Part-Time Faculty Utilization and Its Impact on Student Retention at a Public Research University

ERIC Educational Resources Information Center

Johnson, Iryna Y.

2006-01-01

The important concern surrounding growing reliance on part-time faculty is its effect on student retention. Existing studies explored the relationship between part-time faculty utilization and retention of entering cohorts. The study herein assesses retention of the entire population of degree-seeking undergraduates at a single institution. The…
Effect of the chemical composition and the structural and phases states of materials on hydrogen retention

NASA Astrophysics Data System (ADS)

Chernov, I. I.; Stal'tsov, M. S.; Kalin, B. A.; Bogachev, I. A.; Guseva, L. Yu.; Korshunov, S. N.

2017-07-01

The results of investigation of the effect of chemical composition and structural and phase states of reactor steels and vanadium alloys on their capture and retention of hydrogen introduced into the materials in various ways are presented. It is shown that, in the case of identical conditions of hydrogen introduction, the amount of hydrogen captured by austenitic steels is substantially higher than that captured by ferritic/ martensitic steels. At the same time, the EP450 ODS ferritic/martensitic steel dispersion-strengthened with nanosized yttrium oxide particles retains a substantially higher amount of hydrogen as compared to that retained in the EP450 matrix steel. The alloying of vanadium with tungsten, zirconium, and titanium leads to an increase in the amount of retained hydrogen. The effect of titanium content on hydrogen retention is found to be nonmonotonic; the phenomenon is explained from a physical view point.
Knowledge structures and the acquisition of a complex skill.

PubMed

Day, E A; Arthur, W; Gettman, D

2001-10-01

The purpose of this study was to examine the viability of knowledge structures as an operationalization of learning in the context of a task that required a high degree of skill. Over the course of 3 days, 86 men participated in 9 training sessions and learned a complex video game. At the end of acquisition, participants' knowledge structures were assessed. After a 4-day nonpractice interval, trainees completed tests of skill retention and skill transfer. Findings indicated that the similarity of trainees' knowledge structures to an expert structure was correlated with skill acquisition and was predictive of skill retention and skill transfer. However, the magnitude of these effects was dependent on the method used to derive the expert referent structure. Moreover, knowledge structures mediated the relationship between general cognitive ability and skill-based performance.
The relationship between healthy work environments and retention of nurses in a hospital setting.

PubMed

Ritter, Desiree

2011-01-01

The purpose of the present paper was to determine the effect a healthy work environment has on the retention of nurses in a hospital setting. There is a nursing shortage that has been ongoing and is expected to continue, resulting in challenges for the healthcare system in the United States. The significance of this issue is the impact the nursing shortage will have on healthcare organizations and patients. The present paper included an extensive review of the current literature. The literature reviewed encompassed scholarly peer-reviewed journal articles. This article focused on nurses, work environments and the impact of the work environments on retention. Important issues that emerged from this analysis were the dangers of an unhealthy environment, the impact a healthy work environment has on patient outcomes and retention, the Magnet link to healthy work environments and the manager's role in creating and sustaining a healthy work environment. The literature provided evidence of the link between healthy work environments and the retention of nurses in a hospital setting. The implications for management are to implement changes now to create a healthy work environment that will recruit and retain nurses to secure their position in the future. © 2010 The Author. Journal compilation © 2010 Blackwell Publishing Ltd.
Analysis and prediction of structure-reactive toxicity relationships of substituted aromatic compounds

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

Liu, Z.T.; Wang, L.S.; Chen, S.P.

1996-12-31

The fundamental differentiation of toxicity is between reactive and nonreactive toxicity. Reactive toxicity is associated with a specific mechanism for the reaction with an enzyme or inhibition of a metabolic pathway, and nonreactive toxicity is related directly to the quantity of toxicant acting upon the cell. The quantitative structure-activity relationships (QSARs) have been successfully used in the nonreactive toxicity, such as prediction of the toxicity of nonreactive compounds based on their solubility in the lipids of organisms. The elements of molecular structure that are most closely related to nonreactive toxicity are those that describe the partitioning of the toxicant intomore » the organism, while QSARs for the reactive toxicity are less common in the environmental toxicology literature. With the recent increase in the use of synthetic substituted benzenes as industrial chemicals, the accurate analysis of the effect of reactive toxic chemicals has become recognized with QSAR. For this purpose, we selected the fish (Carassias auratus) as the test organism, measured the acute toxicity of 50% lethal concentration (LC{sub 50}) of the chemicals and the adenosine triphosphate (ATP) content of the liver cells for the organism. These determined the relationships of the acute toxicity of some substituted benzenes with their physicochemical structural parameters. The effects on the ATP content was also compared to predict biological reactivities of the chemicals, so as to find some clues to explain the mode of mechanism of the toxicity. 17 refs., 1 tab.« less
Analyzing chromatographic data using multilevel modeling.

PubMed

Wiczling, Paweł

2018-06-01

It is relatively easy to collect chromatographic measurements for a large number of analytes, especially with gradient chromatographic methods coupled with mass spectrometry detection. Such data often have a hierarchical or clustered structure. For example, analytes with similar hydrophobicity and dissociation constant tend to be more alike in their retention than a randomly chosen set of analytes. Multilevel models recognize the existence of such data structures by assigning a model for each parameter, with its parameters also estimated from data. In this work, a multilevel model is proposed to describe retention time data obtained from a series of wide linear organic modifier gradients of different gradient duration and different mobile phase pH for a large set of acids and bases. The multilevel model consists of (1) the same deterministic equation describing the relationship between retention time and analyte-specific and instrument-specific parameters, (2) covariance relationships relating various physicochemical properties of the analyte to chromatographically specific parameters through quantitative structure-retention relationship based equations, and (3) stochastic components of intra-analyte and interanalyte variability. The model was implemented in Stan, which provides full Bayesian inference for continuous-variable models through Markov chain Monte Carlo methods. Graphical abstract Relationships between log k and MeOH content for acidic, basic, and neutral compounds with different log P. CI credible interval, PSA polar surface area.
Functional Relationships for Investigating Cognitive Processes

PubMed Central

Wright, Anthony A.

2013-01-01

Functional relationships (from systematic manipulation of critical variables) are advocated for revealing fundamental processes of (comparative) cognition—through examples from my work in psychophysics, learning, and memory. Functional relationships for pigeon wavelength (hue) discrimination revealed best discrimination at the spectral points of hue transition for pigeons—a correspondence (i.e., functional relationship) similar to that for humans. Functional relationships for learning revealed: Item-specific or relational learning in matching to sample as a function of the pigeons’ sample-response requirement, and same/different abstract-concept learning as a function of the training set size for rhesus monkeys, capuchin monkeys, and pigeons. Functional relationships for visual memory revealed serial position functions (a 1st order functional relationship) that changed systematically with retention delay (a 2nd order relationship) for pigeons, capuchin monkeys, rhesus monkeys, and humans. Functional relationships for rhesus-monkey auditory memory also revealed systematic changes in serial position functions with delay, but these changes were opposite to those for visual memory. Functional relationships for proactive interference revealed interference that varied as a function of a ratio of delay times. Functional relationships for change detection memory revealed (qualitative) similarities and (quantitative) differences in human and monkey visual short term memory as a function of the number of memory items. It is concluded that these findings were made possible by varying critical variables over a substantial portion of the manipulable range to generate functions and derive relationships. PMID:23174335
Comparative mapping of quantitative trait loci for Fusarium head blight resistance and anther retention in the winter wheat population Capo × Arina.

PubMed

Buerstmayr, Maria; Buerstmayr, Hermann

2015-08-01

Fusarium resistance in Arina is highly quantitative and governed by multiple small effect QTL. Anther retention has a high correlation with FHB susceptibility and appears a practicable indirect selection target for enhancing FHB resistance. The Swiss winter wheat cultivar Arina possesses a high resistance level constituted by a number of small to medium effect QTL reported from three independent mapping populations. Yet these overlap only for one resistance QTL on the long arm of chromosome 1B. The present study characterized Fusarium head blight (FHB) resistance in a population of 171 recombinant inbred lines from a cross between Arina (resistant) and Capo (moderately resistant). The population was evaluated for FHB resistance under field conditions for 3 years. Additionally, we phenotyped anther retention, plant height and flowering date to analyze their association with resistance. Lines with a low proportion of retained anthers after flowering and tall plants were significantly less diseased, while flowering date had no association with FHB severity. QTL analysis identified eight small to medium effect QTL for FHB severity, of which QTL on 1BS, 3B, 4AL and 6BL likely correspond to resistance alleles already detected in previously studied Arina populations. QTL for anther retention mapped to 4AL, 6BL and 5AS. Notably, QTL on 4AL and 6BL overlapped with QTL for FHB severity. A single small effect QTL for plant height was detected on 5AS and no QTL was identified for flowering date. Genotypes having three or four resistance alleles in combination showed a good resistance level, indicating pyramiding resistance QTL as a powerful approach for breeding resistant cultivars. Selection for rapid and complete anther extrusion appears promising as an indirect selection criterion for enhancing FHB resistance.
Ecomorphology of morpho-functional relationships in the family of Sparidae: a quantitative statistic approach.

PubMed

Antonucci, Francesca; Costa, Corrado; Aguzzi, Jacopo; Cataudella, Stefano

2009-07-01

In many fish species, morphological similarity can be considered as a proxy for similarities in habitat use. The Sparidae family includes species that are recognized for common morphological features such as structure and positioning of the fins and specialized dentition. The aim of this study was to quantitatively describe the relationship of body shape morphology with habitat use, trophic level, and systematics in the majority of known Sparidae species (N = 92). This ecomorphological comparison was performed with a geometric morphometric approach considering as variables the Trophic Index (TROPH), the habitat (i.e., classified as demersal, benthopelagic and reef associated) and the phylogenetic relationship of species at the subfamily level. The analysis by the TROPH variable showed a positive relation with shape because the morphological features of all the species are strongly correlated with their trophic behavior (e.g., herbivore species have a smaller mouth gap that make them able to feed upon sessile resources). The morphological analysis according to the Habitat variable was used to classify species according to a feeding-habitat niche in terms of portion of the water column and seabed space where species mostly perform their behavioral activities. We described three kinds of morphological designs in relation to a benthopelagic, demersal and reef-associated habit. The six subfamily groups were morphologically well distinguishable and the cladogram relative to Mahalanobis' morphological distances was compared with those proposed by other authors. We also quantified the phylogenetic relationship among the different subfamilies based on the analysis of shape in relation to trophic ecology, confirming the observations of the authors. (c) 2009 Wiley-Liss, Inc.

The Relationship between SAT Scores and Retention to the Third Year: 2006 Cohort. Statistical Report

ERIC Educational Resources Information Center

Mattern, Krista D.; Patterson, Brian F.

2010-01-01

Results show that SAT performance is related to third year retention rates. Even after controlling for student and institutional characteristics, returners had higher SAT total scores than non-returners, and the performance gap is not due to differences in the demographic makeup of the two groups. Furthermore, while differences in retention can be…
Support vector regression-guided unravelling: antioxidant capacity and quantitative structure-activity relationship predict reduction and promotion effects of flavonoids on acrylamide formation

PubMed Central

Huang, Mengmeng; Wei, Yan; Wang, Jun; Zhang, Yu

2016-01-01

We used the support vector regression (SVR) approach to predict and unravel reduction/promotion effect of characteristic flavonoids on the acrylamide formation under a low-moisture Maillard reaction system. Results demonstrated the reduction/promotion effects by flavonoids at addition levels of 1–10000 μmol/L. The maximal inhibition rates (51.7%, 68.8% and 26.1%) and promote rates (57.7%, 178.8% and 27.5%) caused by flavones, flavonols and isoflavones were observed at addition levels of 100 μmol/L and 10000 μmol/L, respectively. The reduction/promotion effects were closely related to the change of trolox equivalent antioxidant capacity (ΔTEAC) and well predicted by triple ΔTEAC measurements via SVR models (R: 0.633–0.900). Flavonols exhibit stronger effects on the acrylamide formation than flavones and isoflavones as well as their O-glycosides derivatives, which may be attributed to the number and position of phenolic and 3-enolic hydroxyls. The reduction/promotion effects were well predicted by using optimized quantitative structure-activity relationship (QSAR) descriptors and SVR models (R: 0.926–0.994). Compared to artificial neural network and multi-linear regression models, SVR models exhibited better fitting performance for both TEAC-dependent and QSAR descriptor-dependent predicting work. These observations demonstrated that the SVR models are competent for predicting our understanding on the future use of natural antioxidants for decreasing the acrylamide formation. PMID:27586851
Support vector regression-guided unravelling: antioxidant capacity and quantitative structure-activity relationship predict reduction and promotion effects of flavonoids on acrylamide formation

NASA Astrophysics Data System (ADS)

Huang, Mengmeng; Wei, Yan; Wang, Jun; Zhang, Yu

2016-09-01

We used the support vector regression (SVR) approach to predict and unravel reduction/promotion effect of characteristic flavonoids on the acrylamide formation under a low-moisture Maillard reaction system. Results demonstrated the reduction/promotion effects by flavonoids at addition levels of 1-10000 μmol/L. The maximal inhibition rates (51.7%, 68.8% and 26.1%) and promote rates (57.7%, 178.8% and 27.5%) caused by flavones, flavonols and isoflavones were observed at addition levels of 100 μmol/L and 10000 μmol/L, respectively. The reduction/promotion effects were closely related to the change of trolox equivalent antioxidant capacity (ΔTEAC) and well predicted by triple ΔTEAC measurements via SVR models (R: 0.633-0.900). Flavonols exhibit stronger effects on the acrylamide formation than flavones and isoflavones as well as their O-glycosides derivatives, which may be attributed to the number and position of phenolic and 3-enolic hydroxyls. The reduction/promotion effects were well predicted by using optimized quantitative structure-activity relationship (QSAR) descriptors and SVR models (R: 0.926-0.994). Compared to artificial neural network and multi-linear regression models, SVR models exhibited better fitting performance for both TEAC-dependent and QSAR descriptor-dependent predicting work. These observations demonstrated that the SVR models are competent for predicting our understanding on the future use of natural antioxidants for decreasing the acrylamide formation.
Towards cheminformatics-based estimation of drug therapeutic index: Predicting the protective index of anticonvulsants using a new quantitative structure-index relationship approach.

PubMed

Chen, Shangying; Zhang, Peng; Liu, Xin; Qin, Chu; Tao, Lin; Zhang, Cheng; Yang, Sheng Yong; Chen, Yu Zong; Chui, Wai Keung

2016-06-01

The overall efficacy and safety profile of a new drug is partially evaluated by the therapeutic index in clinical studies and by the protective index (PI) in preclinical studies. In-silico predictive methods may facilitate the assessment of these indicators. Although QSAR and QSTR models can be used for predicting PI, their predictive capability has not been evaluated. To test this capability, we developed QSAR and QSTR models for predicting the activity and toxicity of anticonvulsants at accuracy levels above the literature-reported threshold (LT) of good QSAR models as tested by both the internal 5-fold cross validation and external validation method. These models showed significantly compromised PI predictive capability due to the cumulative errors of the QSAR and QSTR models. Therefore, in this investigation a new quantitative structure-index relationship (QSIR) model was devised and it showed improved PI predictive capability that superseded the LT of good QSAR models. The QSAR, QSTR and QSIR models were developed using support vector regression (SVR) method with the parameters optimized by using the greedy search method. The molecular descriptors relevant to the prediction of anticonvulsant activities, toxicities and PIs were analyzed by a recursive feature elimination method. The selected molecular descriptors are primarily associated with the drug-like, pharmacological and toxicological features and those used in the published anticonvulsant QSAR and QSTR models. This study suggested that QSIR is useful for estimating the therapeutic index of drug candidates. Copyright © 2016. Published by Elsevier Inc.
Pore-Scale Effects of Soil Structure And Microbial EPS Production On Soil Water Retention

NASA Astrophysics Data System (ADS)

Orner, E.; Anderson, E.; Rubinstein, R. L.; Chau, J. F.; Shor, L. M.; Gage, D. J.

2013-12-01

Climate-induced changes to the hydrological cycle will increase the frequency of extreme weather events including powerful storms and prolonged droughts. Moving forward, one of the major factors limiting primary productivity in terrestrial ecosystems will be sub-optimal soil moisture. We focus here on the ability of soils to retain moisture under drying conditions. A soil's ability to retain moisture is influenced by many factors including its texture, its structure, and the activities of soil microbes. In soil microcosms, the addition of small amounts of microbially-produced extracellular polymeric substances (EPS) can dramatically shift moisture retention curves. The objective of this research is to better understand how soil structure and EPS may act together to retain moisture in unsaturated soils. Replicate micromodels with exactly-conserved 2-D physical geometry were initially filled with aqueous suspensions of one of two types of bacteria: one mutant was ultra- muccoid and the other was non-muccoid. Replicate micromodels were held at a fixed, external, relative humidity, and the position of the air-water interface was imaged over time as water evaporates. There was no forced convection of air or water inside the micromodels: drying was achieved by water evaporation and diffusion alone. We used a fully automated, inverted microscope to image replicate drying lanes each with dimensions of 1 mm x 10 mm. A complete set of images was collected every 30 minutes for 30 hours. The results show devices loaded with the highly muccoid strain remained >40% hydrated for 13 h, while devices loaded with the non-muccoid remained >40% hydrated for only 6 h, and were completely dry by 13 h. Current work is comparing interfacial water fluxes in structured and unstructured settings, and is attempting to model the synergistic effects of soil structure and EPS content on moisture retention in real soils. This research may allow more accurate description of naturally
Structural empowerment and anticipated turnover among behavioural health nurses.

PubMed

Smith, Thomas; Capitulo, Kathleen Leask; Quinn Griffin, Mary T; Fitzpatrick, Joyce J

2012-07-01

The aim of this pilot study was to examine the relationship between structural empowerment and anticipated turnover among behavioural health nurses. There have been several studies relating structural empowerment to a range of organizational characteristics and personal attributes of nurses themselves. There are also previous studies linking the key variables in the present study, but no previous research of behavioural health nurses was available. A quantitative design was used for this cross-sectional pilot study. All registered nurses (RN) working on inpatient units in the study facility were invited to participate (n = 97). An anonymous survey was sent to all potential participants. The response rate was 53% (n = 50). The majority of participants perceived themselves as moderately empowered. There was a significant negative correlation between empowerment and anticipated turnover. The results of this pilot study among behavioural health nurses are similar to the results among nurses working in other clinical areas. Nurse managers should be cognizant of the factors that enhance nurses' perceptions of empowerment, particularly related to issues of retention and anticipated turnover among behavioural health nurses. © 2012 Blackwell Publishing Ltd.
Improving subject recruitment, retention, and participation in research through Peplau's theory of interpersonal relations.

PubMed

Penckofer, Sue; Byrn, Mary; Mumby, Patricia; Ferrans, Carol Estwing

2011-04-01

Recruitment and retention of persons participating in research is one of the most significant challenges faced by investigators. Although incentives are often used to improve recruitment and retention, evidence suggests that the relationship of the patient to study personnel may be the single, most important factor in subject accrual and continued participation. Peplau's theory of interpersonal relations provides a framework to study the nurse-patient relationship during the research process. In this paper the authors provide a brief summary of research strategies that have been used for the recruitment and retention of subjects and an overview of Peplau's theory of interpersonal relations including its use in research studies. In addition, a discussion of how this theory was used for the successful recruitment and retention of women with type 2 diabetes who participated in a clinical trial using a nurse-delivered psychoeducational intervention for depression is addressed.
The value of mentoring: a strategic approach to retention and recruitment.

PubMed

Greene, Maureen T; Puetzer, Mary

2002-10-01

The issues of recruitment, training, and retention of experienced nursing staff remains an ongoing business strategy of nursing service in many health care facilities. The implementation of a structured mentoring program recognizes the need to develop and maintain relationships between the new and the experienced nurses. The terms of mentor and mentee are defined within a structured orientation program, highlighting specific roles and responsibilities of each. The use of other staff as preceptors and resources is discussed as a mechanism to enhance diversity in skill and knowledge development. The value of clinical tracking forms, planning calendars, and feedback mechanisms are stressed to ensure success in monitoring this program in a longitudinal way. Problems associated with the assignment of mentors are addressed as an area for future investigation in different care settings.
Recruitment and retention of physicians in rural Alberta: the spousal perspective.

PubMed

Myroniuk, Lana; Adamiak, Paul; Bajaj, Sameer; Myhre, Douglas L

2016-01-01

The overall geographic distribution of physicians in Canada, including Alberta, is misaligned with the population distribution. Some strategies, such as debt repayment, are currently in practice to increase recruitment and retention of physicians in rural locations. Of the factors influencing choice of practice location, 'spousal influence' is considered to play a significant role in recruitment and retention of physicians in literature. Most studies have focused on the physicians' perspective of their spouses' influence on staying in a rural location. This study is unique as it approaches rural recruitment and retention from the perspective of the physician spouse. The physician population for this study consisted of doctors practicing in rural southern Alberta. Participants were recruited via an email invitation and were invited to complete an online survey. The survey collected information regarding physician demographics and some relationship characteristics. The email invitation also contained a link to a second survey specific to the physician spouse or partner, asking a similar panel of questions. Physicians were asked to request their spouse or partner to complete this survey. Semi-structured interviews were conducted for those who consented to be contacted for interviews. Descriptive statistical analysis of the survey data was carried out. Thematic analysis of the qualitative interview data was conducted and was organized into three sections. The first and second sections present the personal experiences of rural recruitment and rural retention. The third section presents recommendations made by physicians and spouses to improve these processes. Specific interview quotes led the authors to derive themes under each section. The results of this study raise the voice and profile of the spouse in the process of rural recruitment and retention. In this study, the spouses of Canadian medical graduates were a positive influence in rural recruitment and retention
The influence of salt chaotropicity, column hydrophobicity and analytes' molecular properties on the retention of pramipexole and its impurities.

PubMed

Vemić, Ana; Kalinić, Marko; Erić, Slavica; Malenović, Anđelija; Medenica, Mirjana

2015-03-20

The aim of this study was to examine the interaction of the chaotropic salts of different position in Hofmeister series (CF3COONa, NaClO4, NaPF6) added to the mobile phase with the stationary phases of different hydrophobicity (C8 and C18 XTerra(®) columns), as well as their common influence on the retention behavior of pramipexole and its structurally related impurities. The extended thermodynamic approach enabled the understanding of the underlying separation mechanism. Comparing six different column-salt systems it was observed that general system hydrophobicity presented by salt chaotropicity and column hydrophobicity favors stationary phase ion-pairing over the ion-pair formation in the eluent. Further, an attempt was made to describe the influence of analytes' nature on their retention behavior in such chromatographic systems. An analysis is performed in order to select and elucidate the molecular descriptors (electrostatical, quantum-chemical, geometrical, topological, and constitutional) that best explain the experimental evidence and findings obtained by the thermodynamic approach. The results of this analysis suggest that analytes' charge distribution and its complementarity to the structure of the electric double layer formed on the surface of the stationary phase upon the addition of chaotropic additives can be useful for understanding the differences in retention of structurally related analytes. These findings provide a novel understanding of the interactions between all the components of the chromatographic system containing chaotropic additive and a good basis for further investigations suggesting the development of generally applicable predictors in structure-retention relationship studies in related chromatographic systems. Copyright © 2015 Elsevier B.V. All rights reserved.
College Student Retention: A Self-Determination Perspective

ERIC Educational Resources Information Center

Tetreault, Jules

2013-01-01

This study sought to identify the relationship between a student's level of self-determination towards aspiring to receive a college degree and student retention from the first to second year. Deci & Ryan's (2000) self-determination theory served as the conceptual framework for this study. The fundamental assumption of self-determination is…
The relationship between international trade and non-nutritional health outcomes: A systematic review of quantitative studies.

PubMed

Burns, Darren K; Jones, Andrew P; Suhrcke, Marc

2016-03-01

Markets throughout the world have been reducing barriers to international trade and investment in recent years. The resulting increases in levels of international trade and investment have subsequently generated research interest into the potential population health impact. We present a systematic review of quantitative studies investigating the relationship between international trade, foreign direct investment and non-nutritional health outcomes. Articles were systematically collected from the SCOPUS, PubMed, EconLit and Web of Science databases. Due to the heterogeneous nature of the evidence considered, the 16 included articles were subdivided into individual level data analyses, selected country analyses and international panel analyses. Articles were then quality assessed using a tool developed as part of the project. Nine of the studies were assessed to be high quality, six as medium quality, and one as low quality. The evidence from the quantitative literature suggests that overall, there appears to be a beneficial association between international trade and population health. There was also evidence of the importance of foreign direct investment, yet a lack of research considering the direction of causality. Taken together, quantitative research into the relationship between trade and non-nutritional health indicates trade to be beneficial, yet this body of research is still in its infancy. Future quantitative studies based on this foundation will provide a stronger basis on which to inform relevant national and international institutions about the health consequences of trade policies. Copyright © 2016 Elsevier Ltd. All rights reserved.
Quantitative Structure-Activity Relationship Modeling Coupled with Molecular Docking Analysis in Screening of Angiotensin I-Converting Enzyme Inhibitory Peptides from Qula Casein Hydrolysates Obtained by Two-Enzyme Combination Hydrolysis.

PubMed

Lin, Kai; Zhang, Lanwei; Han, Xue; Meng, Zhaoxu; Zhang, Jianming; Wu, Yifan; Cheng, Dayou

2018-03-28

In this study, Qula casein derived from yak milk casein was hydrolyzed using a two-enzyme combination approach, and high angiotensin I-converting enzyme (ACE) inhibitory activity peptides were screened by quantitative structure-activity relationship (QSAR) modeling integrated with molecular docking analysis. Hydrolysates (<3 kDa) derived from combinations of thermolysin + alcalase and thermolysin + proteinase K demonstrated high ACE inhibitory activities. Peptide sequences in hydrolysates derived from these two combinations were identified by liquid chromatography-tandem mass spectrometry (LC-MS/MS). On the basis of the QSAR modeling prediction, a total of 16 peptides were selected for molecular docking analysis. The docking study revealed that four of the peptides (KFPQY, MPFPKYP, MFPPQ, and QWQVL) bound the active site of ACE. These four novel peptides were chemically synthesized, and their IC 50 was determined. Among these peptides, KFPQY showed the highest ACE inhibitory activity (IC 50 = 12.37 ± 0.43 μM). Our study indicated that Qula casein presents an excellent source to produce ACE inhibitory peptides.
The Value of Academic Libraries: Library Services as a Predictor of Student Retention

ERIC Educational Resources Information Center

Murray, Adam; Ireland, Ashley; Hackathorn, Jana

2016-01-01

This study examined the predictive relationship between library use by individual students and their retention status in university settings. The methodology builds on a small number of previous studies to examine library use at the individual level to determine if use of specific library services is predictive of retention for freshmen and…
The Space Shuttle orbiter payload retention systems

NASA Technical Reports Server (NTRS)

Hardee, J. H.

1982-01-01

Payloads are secured in the orbiter payload bay by the payload retention system or are equipped with their own unique retention systems. The orbiter payload retention mechanisms provide structural attachments for each payload by using four or five attachment points to secure the payload within the orbiter payload bay during all phases of the orbiter mission. The payload retention system (PRS) is an electromechanical system that provides standarized payload carrier attachment fittings to accommodate up to five payloads for each orbiter flight. The mechanisms are able to function under either l-g or zero-g conditions. Payload berthing or deberthing on orbit is accomplished by utilizing the remote manipulator system (RMS). The retention mechanisms provide the capability for either vertical or horizontal payload installation or removal. The payload support points are selected to minimize point torsional, bending, and radial loads imparted to the payloads. In addition to the remotely controlled latching system, the passive system used for nondeployable payloads performs the same function as the RMS except it provides fixed attachments to the orbiter.
The Relationship between Technology Use of Administrators and Technology Use of Teachers: A Quantitative Study

ERIC Educational Resources Information Center

Szafranski, Sandra L.

2009-01-01

The purpose of this quantitative correlational study was to assess the relationship between the level of technology use of administrators and the level of technology use of their teachers. The target sample was principals and teachers in nine schools in three school districts in south central Wisconsin. Participants were from one elementary…
The change in retentive force of magnetic attachment by abrasion.

PubMed

Huang, Yuanjin; Tawada, Yasuyuki; Hata, Yoshiaki; Watanabe, Fumihiko

2008-07-01

Magnets are frequently applied to removable dentures as retentive attachments. A magnet-retained removable overdenture might be slightly shifted from side to side by eccentric movement in the mouth, and the surface of magnetic attachment may be worn as a result. However, the relationship between the retentive force of magnetic attachment and its surface abrasion has not been reported. The purpose of this research is to investigate this relationship. Ten Mgfit DX 400 magnetic attachments for natural tooth roots were used for this experiment. The magnetic attachments were embedded in autopolymerizing acrylic resin, and ten pairs of specimens were fabricated. A 5-mm repeated gliding motion was applied on each pair of specimens until 30 000, 50 000, or 90 000 cycles had been achieved. The abrasion machine was under 5 kg loading, and the slide speed was 60 times/min. The retentive force of magnetic attachment was measured with a tension gauge at (1) before gliding; (2) after 30 000 gliding cycles; (3)after 50 000 gliding cycles; or (4) after 90 000 gliding cycles. The average change of retentive force of ten magnetic attachments after 30 000, 50 000, and 90 000 gliding cycles was 0.016 N, 0.003 N, and -0.008 N, respectively. The change was statistically analyzed using a paired-sample t test, which showed that the number of gliding cycles did not affect the retentive force of magnetic attachment significantly. The surface of magnetic attachment after gliding was observed by a microscope, and the abrasion of this attachment surface is clearly seen.
Influence of phase type and solute structure on changes in retention with pressure in reversed-phase high performance liquid chromatography.

PubMed

Fallas, Morgane M; Tanaka, Nobuo; Buckenmaier, Stephan M C; McCalley, David V

2013-07-05

The influence of pressure on the retention of several types of solute, including acids, bases and neutrals, was studied by the use of restriction capillaries added to the end of various monomeric and polymeric octadecylsilyl-modified 5μm particle size columns. Although it appeared that certain polymeric columns could give somewhat greater increases in retention with pressure, differences in behaviour between these different C18 columns were rather small. Differences in solute molecular size were most important in determining increases in retention with pressure. However, solute structure such as polarity and planarity were also influential. A prototype C30 column gave interesting selectivity changes between planar and non-planar solutes as a function of pressure. Considerable selectivity differences with pressure were shown when diverse mixtures of solutes were analysed. For the solutes studied, only minor effects of increased pressure on column efficiency and peak shape were noted. Copyright © 2013 Elsevier B.V. All rights reserved.
A Novel Two-Step Hierarchial Quantitative Structure-Activity ...

EPA Pesticide Factsheets

Background: Accurate prediction of in vivo toxicity from in vitro testing is a challenging problem. Large public–private consortia have been formed with the goal of improving chemical safety assessment by the means of high-throughput screening. Methods and results: A database containing experimental cytotoxicity values for in vitro half-maximal inhibitory concentration (IC50) and in vivo rodent median lethal dose (LD50) for more than 300 chemicals was compiled by Zentralstelle zur Erfassung und Bewertung von Ersatz- und Ergaenzungsmethoden zum Tierversuch (ZEBET ; National Center for Documentation and Evaluation of Alternative Methods to Animal Experiments) . The application of conventional quantitative structure–activity relationship (QSAR) modeling approaches to predict mouse or rat acute LD50 values from chemical descriptors of ZEBET compounds yielded no statistically significant models. The analysis of these data showed no significant correlation between IC50 and LD50. However, a linear IC50 versus LD50 correlation could be established for a fraction of compounds. To capitalize on this observation, we developed a novel two-step modeling approach as follows. First, all chemicals are partitioned into two groups based on the relationship between IC50 and LD50 values: One group comprises compounds with linear IC50 versus LD50 relationships, and another group comprises the remaining compounds. Second, we built conventional binary classification QSAR models t
Fluid Retention and Rostral Fluid Shift in Sleep-Disordered Breathing.

PubMed

Kasai, Takatoshi

2016-01-01

Sleep-disordered breathing (SDB) is common and adversely affects cardiovascular morbidity and mortality. Despite multifactorial pathogenesis, SDB is prevalent in patients with fluid retention disorders, such as drug-resistant hypertension, end-stage renal disease, and heart failure, suggesting that fluid retention may play a role in the pathogenesis of SDB. During the day, fluid is likely to accumulate in the legs, and upon lying down at night is displaced from the legs. Many data suggest that some of this fluid displaced from the legs may redistribute to the upper body and predispose to SDB. This review article will highlight evidence for a relationship between SDB and fluid retention or rostral fluid shift, and discuss mechanisms that link them.

JT8D engine performance retention

NASA Technical Reports Server (NTRS)

James, A. D.; Weisel, D. R.

1981-01-01

The attractive performance retention characteristics of the JT8D engine are described. Because of its moderate bypass ratio and turbine temperature, and stiff structural design, the performance retention versus flight cycles of the JT8D engine sets a standard that is difficult for other engines to equal. In addition, the significant benefits of refurbishment of the JT8D engine are presented. Cold section refurbishment offers thrust specific fuel consumption improvements of up to 2 percent and payback in less than a year, making a very attractive investment option for the airlines.
Biological plasticity in penguin heat-retention structures.

PubMed

Thomas, Daniel B; Fordyce, R Ewan

2012-02-01

Insulation and vascular heat-retention mechanisms allow penguins to forage for a prolonged time in water that is much cooler than core body temperature. Wing-based heat retention involves a plexus of humeral arteries and veins, which redirect heat to the body core rather than to the wing periphery. The humeral arterial plexus is described here for Eudyptes and Megadyptes, the only extant penguin genera for which wing vascular anatomy had not previously been reported. The erect-crested (Eudyptes sclateri) and yellow-eyed (Megadyptes antipodes) penguins both have a plexus of three humeral arteries on the ventral surface of the humerus. The wing vascular system shows little variation between erect-crested and yellow-eyed penguins, and is generally conserved across the six extant genera of penguins, with the exception of the humeral arterial plexus. The number of humeral arteries within the plexus demonstrates substantial variation and correlates well with wing surface area. Little penguins (Eudyptula minor) have two humeral arteries and a wing surface area of ∼ 75 cm(2) , whereas emperor penguins (Aptenodytes forsteri) have up to 15 humeral arteries and a wing surface area of ∼ 203 cm(2) . Further, the number of humeral arteries has a stronger correlation with wing surface area than with sea water temperature. We propose that thermoregulation has placed the humeral arterial plexus under a strong selection pressure, driving penguins with larger wing surface areas to compensate for heat loss by developing additional humeral arteries. Copyright © 2011 Wiley Periodicals, Inc.
A Quantitative Study of the Relationship between Leadership Practice and Strategic Intentions to Use Cloud Computing

ERIC Educational Resources Information Center

Castillo, Alan F.

2014-01-01

The purpose of this quantitative correlational cross-sectional research study was to examine a theoretical model consisting of leadership practice, attitudes of business process outsourcing, and strategic intentions of leaders to use cloud computing and to examine the relationships between each of the variables respectively. This study…
Influence of the Structure of Molecules of Derivatives of 1,2,4-Triazole and 1,2,4-Triazine on Chromatographic Retention Under Conditions of Reversed Phase HPLC

NASA Astrophysics Data System (ADS)

Karaseva, I. N.; Karasev, M. O.; Nechaeva, O. N.; Kurbatova, S. V.

2018-07-01

The dependence of the chromatographic retention of 1,2,4-triazine and 1,2,4-triazole derivatives from water-acetonitrile solutions over octadecyl silica on the structure of sorbate molecules is studied. The effect the physicochemical parameters and topology of heterocycle molecules have on the retention characteristics under RP HPLC conditions is analyzed.
Total plasma clearance versus urinary plasma clearance of (51)Cr-EDTA in patients with cirrhosis with and without fluid retention.

PubMed

Henriksen, Ulrik L; Hansen, Hanne B; Ring-Larsen, Helmer; Bendtsen, Flemming; Henriksen, Jens H

2015-01-01

In patients with fluid retention, the total plasma clearance of (51)Cr-EDTA (ClP) may overestimate the glomerular filtration rate (GFR). The present study was therefore undertaken in order to compare ClP with the urinary plasma clearance of (51)Cr-EDTA (ClU) in patients with cirrhosis with and without fluid retention. A total of 136 patients with cirrhosis (24 without fluid retention, 112 with ascites) received a quantitative intravenous injection of (51)Cr-EDTA followed by plasma and quantitative urinary samples for 5 hours. ClP was determined from the injected dose relative to the plasma concentration-time area, extrapolated to infinity. ClU was determined as urinary excretion relative to the plasma concentration-time area up to voiding. In patients without fluid retention, the difference between ClP and ClU (ClP - ClU = ClΔ) was mean 4.5 mL/min/1.73 m(2). In patients with ascites, ClΔ was significantly higher (17.6 mL/min/1.73 m(2), p < 0.0001). ClΔ increased with lower values of GFR (r = - 0.458, p < 0.001). Repeated measurements of ClU in a subgroup of patients with fluid retention (n = 25) gave almost identical values. Different types of corrections of one-pool clearance were almost identical with ClP, except for higher clearance values, which were somewhat underestimated by the former. In patients with fluid retention and ascites ClP and corrected one-pool clearance overestimates GFR substantially. Although ClU may underestimate GFR slightly, patients with ascites should collect urine quantitatively in order to obtain a reliable measurement of GFR.
Factors affecting nurse retention at an academic Magnet® hospital.

PubMed

Buffington, Annsley; Zwink, Jennifer; Fink, Regina; Devine, Deborah; Sanders, Carolyn

2012-05-01

: The aim of this study was to examine the factors affecting the retention of registered nurses (RNs) and validate the revised Casey-Fink Nurse Retention Survey (2009). : Creating an organizational culture of retention may reduce nurse turnover. Focusing on why nurses leave and identifying factors why nurses stay are essential. : A descriptive survey design gathered data from RNs with 1 or more years of experience providing direct patient care and employed in inpatient/ambulatory settings in an acute care, academic, Magnet hospital. : There were no statistically significant relationships between nurse respondents' perceptions of work environment/support/encouragement and age or years of experience. However, there were significant differences between inpatient and ambulatory nurse responses in several key areas including job satisfaction, mentorship, and educational support. Overall, nurses reported feeling a lack of support and recognition from managers. Results provide evidence to support improved strategies to foster nurse retention.
External validation of structure-biodegradation relationship (SBR) models for predicting the biodegradability of xenobiotics.

PubMed

Devillers, J; Pandard, P; Richard, B

2013-01-01

Biodegradation is an important mechanism for eliminating xenobiotics by biotransforming them into simple organic and inorganic products. Faced with the ever growing number of chemicals available on the market, structure-biodegradation relationship (SBR) and quantitative structure-biodegradation relationship (QSBR) models are increasingly used as surrogates of the biodegradation tests. Such models have great potential for a quick and cheap estimation of the biodegradation potential of chemicals. The Estimation Programs Interface (EPI) Suite™ includes different models for predicting the potential aerobic biodegradability of organic substances. They are based on different endpoints, methodologies and/or statistical approaches. Among them, Biowin 5 and 6 appeared the most robust, being derived from the largest biodegradation database with results obtained only from the Ministry of International Trade and Industry (MITI) test. The aim of this study was to assess the predictive performances of these two models from a set of 356 chemicals extracted from notification dossiers including compatible biodegradation data. Another set of molecules with no more than four carbon atoms and substituted by various heteroatoms and/or functional groups was also embodied in the validation exercise. Comparisons were made with the predictions obtained with START (Structural Alerts for Reactivity in Toxtree). Biowin 5 and Biowin 6 gave satisfactorily prediction results except for the prediction of readily degradable chemicals. A consensus model built with Biowin 1 allowed the diminution of this tendency.
Quantitative structural MRI for early detection of Alzheimer’s disease

PubMed Central

McEvoy, Linda K; Brewer, James B

2011-01-01

Alzheimer’s disease (AD) is a common progressive neurodegenerative disorder that is not currently diagnosed until a patient reaches the stage of dementia. There is a pressing need to identify AD at an earlier stage, so that treatment, when available, can begin early. Quantitative structural MRI is sensitive to the neurodegeneration that occurs in mild and preclinical AD, and is predictive of decline to dementia in individuals with mild cognitive impairment. Objective evidence of ongoing brain atrophy will be critical for risk/benefit decisions once potentially aggressive, disease-modifying treatments become available. Recent advances have paved the way for the use of quantitative structural MRI in clinical practice, and initial clinical use has been promising. However, further experience with these measures in the relatively unselected patient populations seen in clinical practice is needed to complete translation of the recent enormous advances in scientific knowledge of AD into the clinical realm. PMID:20977326
Quantitative assessment of surface functionality effects on microglial uptake and retention of PAMAM dendrimers

NASA Astrophysics Data System (ADS)

Liaw, Kevin; Gök, Ozgul; DeRidder, Louis B.; Kannan, Sujatha; Kannan, Rangaramanujam M.

2018-04-01

Dendrimers are a promising class of polymeric nanoparticles for delivery of therapeutics and diagnostics. Polyamidoamine (PAMAM) dendrimers have shown significant efficacy in many animal models, with performance dependent on surface functionalities. Understanding the effects of end groups on biological interactions is critical for rational design of dendrimer-mediated therapies. In this study, we quantify the cellular trafficking kinetics (endocytosis and exocytosis) of generation 4 neutral (D4-OH), cationic (D4-NH2), anionic (D3.5-COOH), and generation 6 neutral (D6-OH) PAMAM dendrimers to investigate the nanoscale effects of surface functionality and size on cellular interactions. Resting and LPS-activated microglia were studied due to their central roles in dendrimer therapies for central nervous system disorders. D4-OH exhibits greater cellular uptake and lower retention than the larger D6-OH. D4-OH and D3.5-COOH exhibit similar trafficking kinetics, while D4-NH2 exhibits significant membrane interactions, resulting in faster cell association but lower internalization. Cationic charge may also enhance vesicular escape for greater cellular retention and preferential partitioning to nuclei. LPS activation further improves uptake of dendrimers, with smaller and cationic dendrimers experiencing the greatest increases in uptake compared to resting microglia. These studies have implications for the dependence of trafficking pathway on dendrimer properties and inform the design of dendrimer constructs tailored to specific therapeutic needs. Cationic dendrimers are ideal for delivering genetic materials to nuclei, but toxicity may be a limiting factor. Smaller, neutral dendrimers are best suited for delivering high levels of therapeutics in acute neuroinflammation, while larger or cationic dendrimers provide robust retention for sustained release of therapeutics in longer-term diseases.
NanoDrop Microvolume Quantitation of Nucleic Acids

PubMed Central

Desjardins, Philippe; Conklin, Deborah

2010-01-01

Biomolecular assays are continually being developed that use progressively smaller amounts of material, often precluding the use of conventional cuvette-based instruments for nucleic acid quantitation for those that can perform microvolume quantitation. The NanoDrop microvolume sample retention system (Thermo Scientific NanoDrop Products) functions by combining fiber optic technology and natural surface tension properties to capture and retain minute amounts of sample independent of traditional containment apparatus such as cuvettes or capillaries. Furthermore, the system employs shorter path lengths, which result in a broad range of nucleic acid concentration measurements, essentially eliminating the need to perform dilutions. Reducing the volume of sample required for spectroscopic analysis also facilitates the inclusion of additional quality control steps throughout many molecular workflows, increasing efficiency and ultimately leading to greater confidence in downstream results. The need for high-sensitivity fluorescent analysis of limited mass has also emerged with recent experimental advances. Using the same microvolume sample retention technology, fluorescent measurements may be performed with 2 μL of material, allowing fluorescent assays volume requirements to be significantly reduced. Such microreactions of 10 μL or less are now possible using a dedicated microvolume fluorospectrometer. Two microvolume nucleic acid quantitation protocols will be demonstrated that use integrated sample retention systems as practical alternatives to traditional cuvette-based protocols. First, a direct A260 absorbance method using a microvolume spectrophotometer is described. This is followed by a demonstration of a fluorescence-based method that enables reduced-volume fluorescence reactions with a microvolume fluorospectrometer. These novel techniques enable the assessment of nucleic acid concentrations ranging from 1 pg/ μL to 15,000 ng/ μL with minimal consumption of
Implementing Response to Intervention in Title I Elementary Schools: A Quantitative Study of Teacher Response Relationships

ERIC Educational Resources Information Center

Webster, Katina F.

2012-01-01

General educators and special educators in Title I elementary schools perceive the relationships between principles of RTI and their state RTI framework, the implementation of RTI, and professional development received in RTI differently. A quantitative survey-based research methodology was employed including the use of Cronbach's alpha to…
The National Treatment Improvement Evaluation Study: Retention Analysis.

ERIC Educational Resources Information Center

Orwin, Rob; Williams, Valerie

This study focuses on programmatic factors that predict retention for individuals in drug and alcohol treatment programs through secondary analysis of data from the National Treatment Improvement Evaluation Study (NTIES). It addresses the relationships between completion rates, lengths of stay, and treatment modality. It examines the effect of…
Interspecies quantitative structure-activity relationships (QSARs) for eco-toxicity screening of chemicals: the role of physicochemical properties.

PubMed

Furuhama, A; Hasunuma, K; Aoki, Y

2015-01-01

In addition to molecular structure profiles, descriptors based on physicochemical properties are useful for explaining the eco-toxicities of chemicals. In a previous study we reported that a criterion based on the difference between the partition coefficient (log POW) and distribution coefficient (log D) values of chemicals enabled us to identify aromatic amines and phenols for which interspecies relationships with strong correlations could be developed for fish-daphnid and algal-daphnid toxicities. The chemicals that met the log D-based criterion were expected to have similar toxicity mechanisms (related to membrane penetration). Here, we investigated the applicability of log D-based criteria to the eco-toxicity of other kinds of chemicals, including aliphatic compounds. At pH 10, use of a log POW - log D > 0 criterion and omission of outliers resulted in the selection of more than 100 chemicals whose acute fish toxicities or algal growth inhibition toxicities were almost equal to their acute daphnid toxicities. The advantage of log D-based criteria is that they allow for simple, rapid screening and prioritizing of chemicals. However, inorganic molecules and chemicals containing certain structural elements cannot be evaluated, because calculated log D values are unavailable.
Structural and quantitative expression analyses of HERV gene family in human tissues.

PubMed

Ahn, Kung; Kim, Heui-Soo

2009-08-31

Human endogenous retroviruses (HERVs) have been implicated in the pathogenesis of several human diseases as multi-copy members in the human genome. Their gene expression profiling could provide us with important insights into the pathogenic relationship between HERVs and cancer. In this study, we have evaluated the genomic structure and quantitatively determined the expression patterns in the env gene of a variety of HERV family members located on six specific loci by the RetroTector 10 program, as well as real-time RT-PCR amplification. The env gene transcripts evidenced significant differences in the human tumor/normal adjacent tissues (colon, liver, uterus, lung and testis). As compared to the adjacent normal tissues, high levels of expression were noted in testis tumor tissues for HERV-K, in liver and lung tumor tissues for HERV-R, in liver, lung, and testis tumor tissues for HERV-H, and in colon and liver tumor tissues for HERV-P. These data warrant further studies with larger groups of patients to develop biomarkers for specific human cancers.
Assessing the impact of health literacy on education retention of stroke patients.

PubMed

Sanders, Kalina; Schnepel, Loretta; Smotherman, Carmen; Livingood, William; Dodani, Sunita; Antonios, Nader; Lukens-Bull, Katryne; Balls-Berry, Joyce; Johnson, Yvonne; Miller, Terri; Hodges, Wayne; Falk, Diane; Wood, David; Silliman, Scott

2014-04-10

Inadequate health literacy is a pervasive problem with major implications for reduced health status and health disparities. Despite the role of focused education in both primary and secondary prevention of stroke, the effect of health literacy on stroke education retention has not been reported. We examined the relationship of health literacy to the retention of knowledge after recommended stroke education. This prospective cross-sectional study was conducted at an urban safety-net hospital. Study subjects were patients older than 18 admitted to the hospital stroke unit with a diagnosis of acute ischemic stroke who were able to provide informed consent to participate (N = 100). Health literacy levels were measured by using the short form of Test of Functional Health Literacy in Adults. Patient education was provided to patients at an inpatient stroke unit by using standardized protocols, in compliance with Joint Commission specifications. The education outcomes for poststroke care education, knowledge retention, was assessed for each subject. The effect of health literacy on the Stroke Patient Education Retention scores was assessed by using univariate and multivariate analyses. Of the 100 participating patients, 59% had inadequate to marginal health literacy. Stroke patients who had marginal health literacy (mean score, 7.45; standard deviation [SD], 1.9) or adequate health literacy (mean score, 7.31; SD, 1.76) had statistically higher education outcome scores than those identified as having inadequate health literacy (mean score, 5.58; SD, 2.06). Results from multivariate analysis indicated that adequate health literacy was most predictive of education outcome retention. This study demonstrated a clear relationship between health literacy and stroke education outcomes. Studies are needed to better understand the relationship of health literacy to key educational outcomes for primary or secondary prevention of stroke and to refine stroke education for literacy
The Family Relationships Grid: Measuring Family Structure.

ERIC Educational Resources Information Center

Copeland, Anne P.; And Others

This study examined the Family Relationships Grid (FRG), a new measure of family structure that evaluates alliances, identification, isolation, and the relative strength of sibling and marital relationships. Subjects were 52 female and 35 male adolescents who were recruited through a university course and who each had at least one sibling.…
Studying the relationship between redox and cell growth using quantitative phase imaging (Conference Presentation)

NASA Astrophysics Data System (ADS)

Sridharan, Shamira; Leslie, Matthew T.; Bapst, Natalya; Smith, John; Gaskins, H. Rex; Popescu, Gabriel

2016-03-01

Quantitative phase imaging has been used in the past to study the dry mass of cells and study cell growth under various treatment conditions. However, the relationship between cellular redox and growth rates has not yet been studied in this context. This study employed the recombinant Glrx-roGFP2 redox biosensor targeted to the mitochondrial matrix or cytosolic compartments of A549 lung epithelial carcinoma cells. The Glrx-roGFP2s biosensor consists of a modified GFP protein containing internal cysteine residues sensitive to the local redox environment. The formation/dissolution of sulfide bridges contorts the internal chromophore, dictating corresponding changes in florescence emission that provide direct measures of the local redox potential. Combining 2-channel florescent imaging of the redox sensor with quantitative phase imaging allowed observation of redox homeostasis alongside measurements of cellular mass during full cycles of cellular division. The results indicate that mitochondrial redox showed a stronger inverse correlation with cell growth than cytoplasmic redox states; although redox changes are restricted to a 5% range. We are now studying the relationship between mitochondrial redox and cell growth in an isogenic series of breast cell lines built upon the MCF-10A genetic background that vary both in malignancy and metastatic potential.
Retention of School-Based SLPs: Relationships among Caseload Size, Workload Satisfaction, Job Satisfaction, and Best Practice

ERIC Educational Resources Information Center

Hutchins, Tiffany L.; Howard, Malinda; Prelock, Patricia A.; Belin, Gayle

2010-01-01

Nationally, the shortage of speech-language pathologists (SLPs) in the schools is growing. As such, it is important to understand factors related to the retention of SLPs in this setting. This study expanded on previous research by examining a wider range of factors that may be related to the retention of SLPs including caseload size, workload…
Effective Schools: Teacher Hiring, Assignment, Development, and Retention

ERIC Educational Resources Information Center

Loeb, Susanna; Kalogrides, Demetra; Beteille, Tara

2012-01-01

The literature on effective schools emphasizes the importance of a quality teaching force in improving educational outcomes for students. In this article we use value-added methods to examine the relationship between a school's effectiveness and the recruitment, assignment, development, and retention of its teachers. Our results reveal four key…
Racial Differences in Retention in Residential Substance Abuse Treatment: The Impact on African American Men

ERIC Educational Resources Information Center

Cooper, R. Lyle; MacMaster, Samuel; Rasch, Randolph

2010-01-01

Purpose: This study employed a static group comparison design with 106 men in residential treatment to examine the relationship of race to treatment retention. Methods: A retrospective analysis of retention, by race, including survival analysis, was undertaken. Results: Findings from the study indicated that (a) Caucasian men complete treatment…

Optimizing the Long-Term Retention of Skills: Structural and Analytic Approaches to Skill Maintenance

DTIC Science & Technology

1990-08-01

evidence for a surprising degree of long-term skill retention. We formulated a theoretical framework , focusing on the importance of procedural reinstatement...considerable forgetting over even relatively short retention intervals. We have been able to place these studies in the same general theoretical framework developed
Quantitative structure-toxicity relationship of the aquatic toxicity for various narcotic pollutants using the norm indexes.

PubMed

Wang, Qiang; Jia, Qingzhu; Yan, Lihong; Xia, Shuqian; Ma, Peisheng

2014-08-01

The aquatic toxicity value of hazardous contaminants plays an important role in the risk assessments of aquatic ecosystems. The following study presents a stable and accurate structure-toxicity relationship model based on the norm indexes for the prediction of toxicity value (log(LC50)) for 190 diverse narcotic pollutants (96 h LC50 data for Poecilia reticulata). Research indicates that this new model is very efficient and provides satisfactory results. The suggested prediction model is evidenced by R(2) (square correlation coefficient) and ARD (average relative difference) values of 0.9376 and 10.45%, respectively, for the training set, and 0.9264 and 13.90% for the testing set. Comparison results with reference models demonstrate that this new method, based on the norm indexes proposed in this work, results in significant improvements, both in accuracy and stability for predicting aquatic toxicity values of narcotic pollutants. Copyright © 2014 Elsevier Ltd. All rights reserved.
New optomechanical approach to quantitative characterization of fatigue behavior of dynamically loaded structures

NASA Astrophysics Data System (ADS)

Furlong, Cosme; Pryputniewicz, Ryszard J.

1995-06-01

The basic relationships between stress and strain under cyclic conditions of loading are not at present well understood. It would seem that information of this type is vital for a fundamental approach to understand the fatigue behavior of dynamically loaded structures. In this paper, experimental and computational methods are utilized to study the fatigue behavior of a thin aluminum cantilever plate subjected to dynamic loading. The studies are performed by combining optomechanical and finite element methods. The cantilever plate is loaded periodically by excitation set at a fixed amplitude and at a specific resonance frequency of the plate. By continuously applying this type of loading and using holographic interferometry, the behavior of the plate during a specific period of time is investigated. Quantitative information is obtained from laser vibrometry data which are utilized by a finite element program to calculate strains and stresses assuming a homogeneous and isotropic material and constant strain elements. It is shown that the use of experimental and computational hybrid methodologies allows identification of different zones of the plate that are fatigue critical. This optomechanical approach proves to be a viable tool for understanding of fatigue behavior of mechanical components and for performing optimization of structures subjected to fatigue conditions.
Quantitative NDE of Composite Structures at NASA

NASA Technical Reports Server (NTRS)

Cramer, K. Elliott; Leckey, Cara A. C.; Howell, Patricia A.; Johnston, Patrick H.; Burke, Eric R.; Zalameda, Joseph N.; Winfree, William P.; Seebo, Jeffery P.

2015-01-01

The use of composite materials continues to increase in the aerospace community due to the potential benefits of reduced weight, increased strength, and manufacturability. Ongoing work at NASA involves the use of the large-scale composite structures for spacecraft (payload shrouds, cryotanks, crew modules, etc). NASA is also working to enable the use and certification of composites in aircraft structures through the Advanced Composites Project (ACP). The rapid, in situ characterization of a wide range of the composite materials and structures has become a critical concern for the industry. In many applications it is necessary to monitor changes in these materials over a long time. The quantitative characterization of composite defects such as fiber waviness, reduced bond strength, delamination damage, and microcracking are of particular interest. The research approaches of NASA's Nondestructive Evaluation Sciences Branch include investigation of conventional, guided wave, and phase sensitive ultrasonic methods, infrared thermography and x-ray computed tomography techniques. The use of simulation tools for optimizing and developing these methods is also an active area of research. This paper will focus on current research activities related to large area NDE for rapidly characterizing aerospace composites.
Three-dimensional quantitative structure-activity relationship (3D QSAR) and pharmacophore elucidation of tetrahydropyran derivatives as serotonin and norepinephrine transporter inhibitors

NASA Astrophysics Data System (ADS)

Kharkar, Prashant S.; Reith, Maarten E. A.; Dutta, Aloke K.

2008-01-01

Three-dimensional quantitative structure-activity relationship (3D QSAR) using comparative molecular field analysis (CoMFA) was performed on a series of substituted tetrahydropyran (THP) derivatives possessing serotonin (SERT) and norepinephrine (NET) transporter inhibitory activities. The study aimed to rationalize the potency of these inhibitors for SERT and NET as well as the observed selectivity differences for NET over SERT. The dataset consisted of 29 molecules, of which 23 molecules were used as the training set for deriving CoMFA models for SERT and NET uptake inhibitory activities. Superimpositions were performed using atom-based fitting and 3-point pharmacophore-based alignment. Two charge calculation methods, Gasteiger-Hückel and semiempirical PM3, were tried. Both alignment methods were analyzed in terms of their predictive abilities and produced comparable results with high internal and external predictivities. The models obtained using the 3-point pharmacophore-based alignment outperformed the models with atom-based fitting in terms of relevant statistics and interpretability of the generated contour maps. Steric fields dominated electrostatic fields in terms of contribution. The selectivity analysis (NET over SERT), though yielded models with good internal predictivity, showed very poor external test set predictions. The analysis was repeated with 24 molecules after systematically excluding so-called outliers (5 out of 29) from the model derivation process. The resulting CoMFA model using the atom-based fitting exhibited good statistics and was able to explain most of the selectivity (NET over SERT)-discriminating factors. The presence of -OH substituent on the THP ring was found to be one of the most important factors governing the NET selectivity over SERT. Thus, a 4-point NET-selective pharmacophore, after introducing this newly found H-bond donor/acceptor feature in addition to the initial 3-point pharmacophore, was proposed.
Quantitative Structure-Cytotoxicity Relationship of Bioactive Heterocycles by the Semi-empirical Molecular Orbital Method with the Concept of Absolute Hardness

NASA Astrophysics Data System (ADS)

Ishihara, Mariko; Sakagami, Hiroshi; Kawase, Masami; Motohashi, Noboru

The relationship between the cytotoxicity of N-heterocycles (13 4-trifluoromethylimidazole, 15 phenoxazine and 12 5-trifluoromethyloxazole derivatives), O-heterocycles (11 3-formylchromone and 20 coumarin derivatives) and seven vitamin K2 derivatives against eight tumor cell lines (HSC-2, HSC-3, HSC-4, T98G, HSG, HepG2, HL-60, MT-4) and a maximum of 15 chemical descriptors was investigated using CAChe Worksystem 4.9 project reader. After determination of the conformation of these compounds and approximation to the molecular form present in vivo (biomimetic) by CONFLEX5, the most stable structure was determined by CAChe Worksystem 4.9 MOPAC (PM3). The present study demonstrates the best relationship between the cytotoxic activity and molecular shape or molecular weight of these compounds. Their biological activities can be estimated by hardness and softness, and by using η-χ activity diagrams.
Local structure in LaMnO3 and CaMnO3 perovskites: A quantitative structural refinement of Mn K -edge XANES data

NASA Astrophysics Data System (ADS)

Monesi, C.; Meneghini, C.; Bardelli, F.; Benfatto, M.; Mobilio, S.; Manju, U.; Sarma, D. D.

2005-11-01

Hole-doped perovskites such as La1-xCaxMnO3 present special magnetic and magnetotransport properties, and it is commonly accepted that the local atomic structure around Mn ions plays a crucial role in determining these peculiar features. Therefore experimental techniques directly probing the local atomic structure, like x-ray absorption spectroscopy (XAS), have been widely exploited to deeply understand the physics of these compounds. Quantitative XAS analysis usually concerns the extended region [extended x-ray absorption fine structure (EXAFS)] of the absorption spectra. The near-edge region [x-ray absorption near-edge spectroscopy (XANES)] of XAS spectra can provide detailed complementary information on the electronic structure and local atomic topology around the absorber. However, the complexity of the XANES analysis usually prevents a quantitative understanding of the data. This work exploits the recently developed MXAN code to achieve a quantitative structural refinement of the Mn K -edge XANES of LaMnO3 and CaMnO3 compounds; they are the end compounds of the doped manganite series LaxCa1-xMnO3 . The results derived from the EXAFS and XANES analyses are in good agreement, demonstrating that a quantitative picture of the local structure can be obtained from XANES in these crystalline compounds. Moreover, the quantitative XANES analysis provides topological information not directly achievable from EXAFS data analysis. This work demonstrates that combining the analysis of extended and near-edge regions of Mn K -edge XAS spectra could provide a complete and accurate description of Mn local atomic environment in these compounds.
Discrepancies between explicit and implicit self-esteem: implications for mate retention strategies and perceived infidelity.

PubMed

Zeigler-Hill, Virgil; Fulton, Jessica J; McLemore, Chandler

2012-01-01

The purpose of the present study was to examine whether the association between explicit self-esteem and relationship outcomes was moderated by implicit self-esteem. This was accomplished by asking 210 undergraduates who were currently involved in romantic relationships to complete measures of their explicit self-esteem, implicit self-esteem, mate retention strategies, and likelihood of future infidelity. Implicit self-esteem was found to moderate the association between high explicit self-esteem and relationship outcomes for male participants such that men with discrepant high self-esteem (i.e., high explicit self-esteem but low implicit self-esteem) reported less use of mate retention strategies and perceived a greater likelihood of future infidelity in their relationships during the next year. These findings provide additional support for the idea that fragile self-esteem may have consequences for the manner in which individuals perceive their relationships.
Are Flunkers Social Outcasts? A Multilevel Study of Grade Retention Effects on Same-Grade Friendships

ERIC Educational Resources Information Center

Demanet, Jannick; Van Houtte, Mieke

2016-01-01

We examine the association between grade retention and the number of same-grade friendships. Moreover, we investigate the effect of a school's proportion of retained students on these friendships and the moderating effect of this school characteristic on the relationship between retention and the number of same-grade friendships. Multilevel…
Rapid Scanning Structure-Activity Relationships in Combinatorial Data Sets: Identification of Activity Switches

PubMed Central

Medina-Franco, José L.; Edwards, Bruce S.; Pinilla, Clemencia; Appel, Jon R.; Giulianotti, Marc A.; Santos, Radleigh G.; Yongye, Austin B.; Sklar, Larry A.; Houghten, Richard A.

2013-01-01

We present a general approach to describe the structure-activity relationships (SAR) of combinatorial data sets with activity for two biological endpoints with emphasis on the rapid identification of substitutions that have a large impact on activity and selectivity. The approach uses Dual-Activity Difference (DAD) maps that represent a visual and quantitative analysis of all pairwise comparisons of one, two, or more substitutions around a molecular template. Scanning the SAR of data sets using DAD maps allows the visual and quantitative identification of activity switches defined as specific substitutions that have an opposite effect on the activity of the compounds against two targets. The approach also rapidly identifies single- and double-target R-cliffs, i.e., compounds where a single or double substitution around the central scaffold dramatically modifies the activity for one or two targets, respectively. The approach introduced in this report can be applied to any analogue series with two biological activity endpoints. To illustrate the approach, we discuss the SAR of 106 pyrrolidine bis-diketopiperazines tested against two formylpeptide receptors obtained from positional scanning deconvolution methods of mixture-based libraries. PMID:23705689
ORTHODONTIC RETENTION. Studies of retention capacity, cost-effectiveness and long-term stability.

PubMed

Tynelius, Gudrun Edman

2014-01-01

Retention strategies, cost-effectiveness and long-term stability of treatment outcome are essential aspects of orthodontic treatment planning. The overall aim of this thesis was to compare and evaluate three different retention strategies, with special reference to short- and long-term clinical stability and cost-effectiveness. The approach was evidence-based, hence randomized controlled methodology was used in order to generate high levels of evidence. This thesis is based on four studies: Papers I and II are based on randomized controlled trials, evaluating the stability of treatment outcome after one and two years of retention, using three different retention strategies: a maxillary vacuum-formed retainer combined with a mandibular canine-to-canine retainer; a maxillary vacuum-formed retainer combined with stripping of the mandibular anterior teeth and a prefabricated positioner. Paper III presents a cost-minimization analysis of two years of retention treatment. Paper IV is based on a randomized controlled trial documenting the results five years post-retention. The following conclusions were drawn: Papers I and II. From a clinical perspective, asssessment after one year of retention disclosed that the three retention methods were successful in retaining the orthodontic treatment results. After two years of retention, all three retention methods were equally effective in controlling relapse at a clinically acceptable level. Most of the relapse occurred during the first year of retention; only minor or negligible changes were found during the second year. The subjects were grouped according to the level of compliance (excellent or good). After two years of retention there was a negative correlation between growth in body height and relapse of mandibular LII in the group of subjects with excellent compliance. The group with good compliance showed a positive correlation (Paper II, Figure 3). After two years of retention, growth in body height, initial crowding and
Structure/activity relationships for biodegradability and their role in environmental assessment

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

Boethling, R.S.

1994-12-31

Assessment of biodegradability is an important part of the review process for both new and existing chemicals under the Toxic Substances Control Act. It is often necessary to estimate biodegradability because experimental data are unavailable. Structure/biodegradability relationships (SBR) are a means to this end. Quantitative SBR have been developed, but this approach has not been very useful because they apply only to a few narrowly defined classes of chemicals. In response to the need for more widely applicable methods, multivariate analysis has been used to develop biodegradability classification models. For example, recent efforts have produced four new models. Two calculatemore » the probability of rapid biodegradation and can be used for classification; the other two models allow semi-quantitative estimation of primary and ultimate biodegradation rates. All are based on multiple regressions against 36 preselected substructures plus molecular weight. Such efforts have been fairly successful by statistical criteria, but in general are hampered by a lack of large and consistent datasets. Knowledge-based expert systems may represent the next step in the evolution of SBR. In principle such systems need not be as severely limited by imperfect datasets. However, the codification of expert knowledge and reasoning is a critical prerequisite. Results of knowledge acquisition exercises and modeling based on them will also be described.« less
A New Perspective on Nursing Retention: Job Embeddedness in Acute Care Nurses.

PubMed

Hopson, Michelle; Petri, Laura; Kufera, Joseph

Job embeddedness considers job satisfaction while incorporating the concepts of environment and community. This exploratory, mixed methods study used the Job Embeddedness Instrument to examine factors that influence retention of acute care nurses. Qualitative methods informed the survey results. Increasing age, ties to community, and peer relationships were found to be most indicative of job embeddedness. Nursing professional development practitioners can impact retention by focusing on factors that encourage nurses to stay in their positions.
The Impact of Mentor Leadership Styles on First-Year Adult Student Retention

ERIC Educational Resources Information Center

Smith Staley, Charlesetta

2012-01-01

This quantitative study explored the leadership styles of mentors for retained first-year adult students to analyze whether the prevalent style had a higher impact on first-year adult student retention. The Multifactor Leadership Questionnaire (MLQ) 5x was used to collect data on the mentors' leadership styles from the perspective of retained…
The Long-Term Effects of Florida's Third Grade Retention Policy

ERIC Educational Resources Information Center

Smith, Andre K.

2016-01-01

The purpose of this quantitative causal-comparative study was to evaluate the long-term effects of Florida's Third-Grade Retention policy on low performing students' subsequent academic performance as measured by FCAT reading scores. The study included a random stratified sample of 1500 retained third graders for failure to meet Florida's…
The importance of forest structure to biodiversity–productivity relationships

PubMed Central

Huth, Andreas

2017-01-01

While various relationships between productivity and biodiversity are found in forests, the processes underlying these relationships remain unclear and theory struggles to coherently explain them. In this work, we analyse diversity–productivity relationships through an examination of forest structure (described by basal area and tree height heterogeneity). We use a new modelling approach, called ‘forest factory’, which generates various forest stands and calculates their annual productivity (above-ground wood increment). Analysing approximately 300 000 forest stands, we find that mean forest productivity does not increase with species diversity. Instead forest structure emerges as the key variable. Similar patterns can be observed by analysing 5054 forest plots of the German National Forest Inventory. Furthermore, we group the forest stands into nine forest structure classes, in which we find increasing, decreasing, invariant and even bell-shaped relationships between productivity and diversity. In addition, we introduce a new index, called optimal species distribution, which describes the ratio of realized to the maximal possible productivity (by shuffling species identities). The optimal species distribution and forest structure indices explain the obtained productivity values quite well (R2 between 0.7 and 0.95), whereby the influence of these attributes varies within the nine forest structure classes. PMID:28280550
Economic implications for management of structural retention on harvest units at the Blue River Ranger District, Willamette National Forest, Oregon.

Treesearch

James F. Weigand; A. Lynn Burditt

1992-01-01

Timber sales offered at the Blue River Ranger District since the 1988 introduction of management for stand structural retention were studied to describe and quantify, where possible, economic implications of that management. Values for the potential lumber from merchantable green trees ranged from $102 to $1114 per acre among the harvest units surveyed thus far....
Enhanced protein retention on poly(caprolactone) via surface initiated polymerization of acrylamide

NASA Astrophysics Data System (ADS)

Ma, Yuhao; Cai, Mengtan; He, Liu; Luo, Xianglin

2016-01-01

To enhance the biocompatibility or extend the biomedical application of poly(caprolactone) (PCL), protein retention on PCL surface is often required. In this study, poly(acrylamide) (PAAm) brushes were grown from PCL surface via surface-initiated atom transfer radical polymerization (SI-ATRP) and served as a protein-capturing platform. Grafted PAAm was densely packed on surface and exhibited superior protein retention ability. Captured protein was found to be resistant to washing under detergent environment. Furthermore, protein structure after being captured was investigated by circular dichroism (CD) spectroscopy, and the CD spectra verified that secondary structure of captured proteins was maintained, indicating no denaturation of protein happened for retention process.
Nanofiltration Membranes for Water Purification: structure-transport relationships and applications

NASA Astrophysics Data System (ADS)

Jons, Steven; Paul, Mou; Matthews, Tamlin; Hailemariam, Leaelaf

Nanofiltration (NF) membranes are used for separating salts and small neutral molecules. NF membranes show unique selectivity properties compared to reverse osmosis membranes as it can selectively pass monovalent salts and neutral molecules as a function of charge and molecular weight cut-off which are dependent on membrane characteristics and operating conditions. Dow Water & Process solutions has been a pioneer in the membrane based water purification field and Dow's role was instrumental in developing several NF membranes for different applications. However, the characterization of NF membranes and hence the development of structure-property relationship is challenging due to the nanoscale thin, crosslinked nature of the membrane. Recently significant efforts were employed to develop analytical capabilities to understand polymer structure and composition and it had been possible to achieve a structure-property relationship for NF membranes. This paper will highlight similar relationships and will also focus on the relationships of membrane structure with membrane transport properties and how this relationship influences products for different application areas such as in oil field, sweetener and minimum liquid discharge etc.
Relative contributions of set-asides and tree retention to the long-term availability of key forest biodiversity structures at the landscape scale.

PubMed

Roberge, Jean-Michel; Lämås, Tomas; Lundmark, Tomas; Ranius, Thomas; Felton, Adam; Nordin, Annika

2015-05-01

Over previous decades new environmental measures have been implemented in forestry. In Fennoscandia, forest management practices were modified to set aside conservation areas and to retain trees at final felling. In this study we simulated the long-term effects of set-aside establishment and tree retention practices on the future availability of large trees and dead wood, two forest structures of documented importance to biodiversity conservation. Using a forest decision support system (Heureka), we projected the amounts of these structures over 200 years in two managed north Swedish landscapes, under management scenarios with and without set-asides and tree retention. In line with common best practice, we simulated set-asides covering 5% of the productive area with priority to older stands, as well as ∼5% green-tree retention (solitary trees and forest patches) including high-stump creation at final felling. We found that only tree retention contributed to substantial increases in the future density of large (DBH ≥35 cm) deciduous trees, while both measures made significant contributions to the availability of large conifers. It took more than half a century to observe stronger increases in the densities of large deciduous trees as an effect of tree retention. The mean landscape-scale volumes of hard dead wood fluctuated widely, but the conservation measures yielded values which were, on average over the entire simulation period, about 2.5 times as high as for scenarios without these measures. While the density of large conifers increased with time in the landscape initially dominated by younger forest, best practice conservation measures did not avert a long-term decrease in large conifer density in the landscape initially comprised of more old forest. Our results highlight the needs to adopt a long temporal perspective and to consider initial landscape conditions when evaluating the large-scale effects of conservation measures on forest biodiversity

Tannin structural elucidation and quantitative ³¹P NMR analysis. 1. Model compounds.

PubMed

Melone, Federica; Saladino, Raffaele; Lange, Heiko; Crestini, Claudia

2013-10-02

Tannins and flavonoids are secondary metabolites of plants that display a wide array of biological activities. This peculiarity is related to the inhibition of extracellular enzymes that occurs through the complexation of peptides by tannins. Not only the nature of these interactions, but more fundamentally also the structure of these heterogeneous polyphenolic molecules are not completely clear. This first paper describes the development of a new analytical method for the structural characterization of tannins on the basis of tannin model compounds employing an in situ labeling of all labile H groups (aliphatic OH, phenolic OH, and carboxylic acids) with a phosphorus reagent. The ³¹P NMR analysis of ³¹P-labeled samples allowed the unprecedented quantitative and qualitative structural characterization of hydrolyzable tannins, proanthocyanidins, and catechin tannin model compounds, forming the foundations for the quantitative structural elucidation of a variety of actual tannin samples described in part 2 of this series.
A simple approximation for larval retention around reefs

NASA Astrophysics Data System (ADS)

Cetina-Heredia, Paulina; Connolly, Sean R.

2011-09-01

Estimating larval retention at individual reefs by local scale three-dimensional flows is a significant problem for understanding, and predicting, larval dispersal. Determining larval dispersal commonly involves the use of computationally demanding and expensively calibrated/validated hydrodynamic models that resolve reef wake eddies. This study models variation in larval retention times for a range of reef shapes and circulation regimes, using a reef-scale three-dimensional hydrodynamic model. It also explores how well larval retention time can be estimated based on the "Island Wake Parameter", a measure of the degree of flow turbulence in the wake of reefs that is a simple function of flow speed, reef dimension, and vertical diffusion. The mean residence times found in the present study (0.48-5.64 days) indicate substantial potential for self-recruitment of species whose larvae are passive, or weak swimmers, for the first several days after release. Results also reveal strong and significant relationships between the Island Wake Parameter and mean residence time, explaining 81-92% of the variability in retention among reefs across a range of unidirectional flow speeds and tidal regimes. These findings suggest that good estimates of larval retention may be obtained from relatively coarse-scale characteristics of the flow, and basic features of reef geomorphology. Such approximations may be a valuable tool for modeling connectivity and meta-population dynamics over large spatial scales, where explicitly characterizing fine-scale flows around reef requires a prohibitive amount of computation and extensive model calibration.
A Relationship Study on Retention among Traditional and Non-Traditional Students in Select North Carolina Community Colleges

ERIC Educational Resources Information Center

Harpe, J. Michael

2010-01-01

Student retention has become one of the most significant issues facing higher education. Countless hours and considerable amounts of money have been spent in an attempt to determine why some students leave college and while others persist. Previous retention studies have focused primarily on traditional students from four-year, residential…
Factors Affecting Student Retention in Online Courses: Overcoming This Critical Problem

ERIC Educational Resources Information Center

Gaytan, Jorge

2013-01-01

The purpose of this study was to determine what a panel of 15 experts would identify as critical factors affecting student retention in online courses that will serve as implications for educational leaders to guide their student retention strategies, online organizational structures, institutional policies, and online instructional activities. A…
Enhanced methodology for porting ion chromatography retention data.

PubMed

Park, Soo Hyun; Shellie, Robert A; Dicinoski, Greg W; Schuster, Georg; Talebi, Mohammad; Haddad, Paul R; Szucs, Roman; Dolan, John W; Pohl, Christopher A

2016-03-04

Porting is a powerful methodology to recalibrate an existing database of ion chromatography (IC) retention times by reflecting the changes of column behavior resulting from either batch-to-batch variability in the production of the column or the manufacture of new versions of a column. This approach has been employed to update extensive databases of retention data of inorganic and organic anions forming part of the "Virtual Column" software marketed by Thermo Fisher Scientific, which is the only available commercial optimization tool for IC separation. The current porting process is accomplished by performing three isocratic separations with two representative analyte ions in order to derive a porting equation which expresses the relationship between old and new data. Although the accuracy of retention prediction is generally enhanced on new columns, errors were observed on some columns. In this work, the porting methodology was modified in order to address this issue, where the porting equation is now derived by using six representative analyte ions (chloride, bromide, iodide, perchlorate, sulfate, and thiosulfate). Additionally, the updated porting methodology has been applied on three Thermo Fisher Scientific columns (AS20, AS19, and AS11HC). The proposed approach showed that the new porting methodology can provide more accurate and robust retention prediction on a wide range of columns, where average errors in retention times for ten test anions under three eluent conditions were less than 1.5%. Moreover, the retention prediction using this new approach provided an acceptable level of accuracy on a used column exhibiting changes in ion-exchange capacity. Crown Copyright © 2016. Published by Elsevier B.V. All rights reserved.
Actual drawing of histological images improves knowledge retention.

PubMed

Balemans, Monique C M; Kooloos, Jan G M; Donders, A Rogier T; Van der Zee, Catharina E E M

2016-01-01

Medical students have to process a large amount of information during the first years of their study, which has to be retained over long periods of nonuse. Therefore, it would be beneficial when knowledge is gained in a way that promotes long-term retention. Paper-and-pencil drawings for the uptake of form-function relationships of basic tissues has been a teaching tool for a long time, but now seems to be redundant with virtual microscopy on computer-screens and printers everywhere. Several studies claimed that, apart from learning from pictures, actual drawing of images significantly improved knowledge retention. However, these studies applied only immediate post-tests. We investigated the effects of actual drawing of histological images, using randomized cross-over design and different retention periods. The first part of the study concerned esophageal and tracheal epithelium, with 384 medical and biomedical sciences students randomly assigned to either the drawing or the nondrawing group. For the second part of the study, concerning heart muscle cells, students from the previous drawing group were now assigned to the nondrawing group and vice versa. One, four, and six weeks after the experimental intervention, the students were given a free recall test and a questionnaire or drawing exercise, to determine the amount of knowledge retention. The data from this study showed that knowledge retention was significantly improved in the drawing groups compared with the nondrawing groups, even after four or six weeks. This suggests that actual drawing of histological images can be used as a tool to improve long-term knowledge retention. © 2015 American Association of Anatomists.
Applications of genetic algorithms on the structure-activity relationship analysis of some cinnamamides.

PubMed

Hou, T J; Wang, J M; Liao, N; Xu, X J

1999-01-01

Quantitative structure-activity relationships (QSARs) for 35 cinnamamides were studied. By using a genetic algorithm (GA), a group of multiple regression models with high fitness scores was generated. From the statistical analyses of the descriptors used in the evolution procedure, the principal features affecting the anticonvulsant activity were found. The significant descriptors include the partition coefficient, the molar refraction, the Hammet sigma constant of the substituents on the benzene ring, and the formation energy of the molecules. It could be found that the steric complementarity and the hydrophobic interaction between the inhibitors and the receptor were very important to the biological activity, while the contribution of the electronic effect was not so obvious. Moreover, by construction of the spline models for these four principal descriptors, the effective range for each descriptor was identified.
Maximizing retention with high risk participants in a clinical trial.

PubMed

Kim, Romina; Hickman, Norval; Gali, Kathleen; Orozco, Nicholas; Prochaska, Judith J

2014-01-01

To describe effective retention strategies in a clinical trial with a high risk, low-income, and vulnerable patient population with serious mental illness. Follow-up assessments were conducted for a randomized clinical tobacco treatment trial at 3, 6, and 12 months postbaseline. Initial follow-up rates of <40% at 3 months led to implementation of proactive retention strategies including obtaining extensive contact information; building relationships with case managers and social workers; contacting jails and prisons; text messaging, e-mailing, and messaging via social networking sites; identifying appointments via electronic medical record; and field outreach to treatment facilities, residences, and parks. Large urban public hospital. Participants were current smokers recruited from 100% smoke-free locked psychiatry units. Assessments covered demographics, substance use, and mental health functioning. Retention rates were plotted over time in relation to key retention strategies. Chi-square and t-tests were used to examine participant predictors of retention at each follow-up. At the 12-month follow-up, the retention strategies that most frequently led to assessment completion were identified. The sample (N = 100) was 65% male; age x = 39.5 years (SD = 11.3); 44% non-Hispanic white; 46% on Medicaid and 34% uninsured; 79% unemployed; and 48% unstably housed. Proactive retention strategies dramatically increased follow-up rates, concluding at 3 months = 82.65%, 6 months = 89.69%, and 12 months = 92.78%. Married and divorced/separated/widowed participants, those with higher income, and participants with alcohol or illicit drug problems had increased retention from 3- to 12-month follow-up. Follow-up rates improved as proactive methods to contact participants were implemented. Dedicated research staff, multiple methods, community networking, and outreach within drug treatment settings improved retention.
Toward the prediction of class I and II mouse major histocompatibility complex-peptide-binding affinity: in silico bioinformatic step-by-step guide using quantitative structure-activity relationships.

PubMed

Hattotuwagama, Channa K; Doytchinova, Irini A; Flower, Darren R

2007-01-01

Quantitative structure-activity relationship (QSAR) analysis is a cornerstone of modern informatics. Predictive computational models of peptide-major histocompatibility complex (MHC)-binding affinity based on QSAR technology have now become important components of modern computational immunovaccinology. Historically, such approaches have been built around semiqualitative, classification methods, but these are now giving way to quantitative regression methods. We review three methods--a 2D-QSAR additive-partial least squares (PLS) and a 3D-QSAR comparative molecular similarity index analysis (CoMSIA) method--which can identify the sequence dependence of peptide-binding specificity for various class I MHC alleles from the reported binding affinities (IC50) of peptide sets. The third method is an iterative self-consistent (ISC) PLS-based additive method, which is a recently developed extension to the additive method for the affinity prediction of class II peptides. The QSAR methods presented here have established themselves as immunoinformatic techniques complementary to existing methodology, useful in the quantitative prediction of binding affinity: current methods for the in silico identification of T-cell epitopes (which form the basis of many vaccines, diagnostics, and reagents) rely on the accurate computational prediction of peptide-MHC affinity. We have reviewed various human and mouse class I and class II allele models. Studied alleles comprise HLA-A*0101, HLA-A*0201, HLA-A*0202, HLA-A*0203, HLA-A*0206, HLA-A*0301, HLA-A*1101, HLA-A*3101, HLA-A*6801, HLA-A*6802, HLA-B*3501, H2-K(k), H2-K(b), H2-D(b) HLA-DRB1*0101, HLA-DRB1*0401, HLA-DRB1*0701, I-A(b), I-A(d), I-A(k), I-A(S), I-E(d), and I-E(k). In this chapter we show a step-by-step guide into predicting the reliability and the resulting models to represent an advance on existing methods. The peptides used in this study are available from the AntiJen database (http://www.jenner.ac.uk/AntiJen). The PLS method
Addressing the crisis of GP recruitment and retention: a systematic review.

PubMed

Marchand, Catherine; Peckham, Stephen

2017-04-01

The numbers of GPs and training places in general practice are declining, and retaining GPs in their practices is an increasing problem. To identify evidence on different approaches to retention and recruitment of GPs, such as intrinsic versus extrinsic motivational determinants. Synthesis of qualitative and quantitative research using seven electronic databases from 1990 onwards (Medline, Embase, Cochrane Library, Health Management Information Consortium [HMIC], Cumulative Index to Nursing and Allied Health Literature (Cinahl), PsycINFO, and the Turning Research Into Practice [TRIP] database). A qualitative approach to reviewing the literature on recruitment and retention of GPs was used. The studies included were English-language studies from Organisation for Economic Cooperation and Development countries. The titles and abstracts of 138 articles were reviewed and analysed by the research team. Some of the most important determinants to increase recruitment in primary care were early exposure to primary care practice, the fit between skills and attributes, and a significant experience in a primary care setting. Factors that seemed to influence retention were subspecialisation and portfolio careers, and job satisfaction. The most important determinants of recruitment and retention were intrinsic and idiosyncratic factors, such as recognition, rather than extrinsic factors, such as income. Although the published evidence relating to GP recruitment and retention is limited, and most focused on attracting GPs to rural areas, the authors found that there are clear overlaps between strategies to increase recruitment and retention. Indeed, the most influential factors are idiosyncratic and intrinsic to the individuals. © British Journal of General Practice 2017.
Addressing the crisis of GP recruitment and retention: a systematic review

PubMed Central

Marchand, Catherine; Peckham, Stephen

2017-01-01

Background The numbers of GPs and training places in general practice are declining, and retaining GPs in their practices is an increasing problem. Aim To identify evidence on different approaches to retention and recruitment of GPs, such as intrinsic versus extrinsic motivational determinants. Design and setting Synthesis of qualitative and quantitative research using seven electronic databases from 1990 onwards (Medline, Embase, Cochrane Library, Health Management Information Consortium [HMIC], Cumulative Index to Nursing and Allied Health Literature (Cinahl), PsycINFO, and the Turning Research Into Practice [TRIP] database). Method A qualitative approach to reviewing the literature on recruitment and retention of GPs was used. The studies included were English-language studies from Organisation for Economic Cooperation and Development countries. The titles and abstracts of 138 articles were reviewed and analysed by the research team. Results Some of the most important determinants to increase recruitment in primary care were early exposure to primary care practice, the fit between skills and attributes, and a significant experience in a primary care setting. Factors that seemed to influence retention were subspecialisation and portfolio careers, and job satisfaction. The most important determinants of recruitment and retention were intrinsic and idiosyncratic factors, such as recognition, rather than extrinsic factors, such as income. Conclusion Although the published evidence relating to GP recruitment and retention is limited, and most focused on attracting GPs to rural areas, the authors found that there are clear overlaps between strategies to increase recruitment and retention. Indeed, the most influential factors are idiosyncratic and intrinsic to the individuals. PMID:28289014
Rational design, synthesis, biologic evaluation, and structure-activity relationship studies of novel 1-indanone alpha(1)-adrenoceptor antagonists.

PubMed

Li, Minyong; Xia, Lin

2007-11-01

In the present report, a novel series of 1-indanone alpha(1)-adrenoceptor antagonists were designed and synthesized based on 3D-pharmacophore model. Their in vitro alpha(1)-adrenoceptor antagonistic assay showed that three compounds (2a, 2m, and 2o) had similar or improved alpha(1)-adrenoceptor antagonistic activities relative to the positive control prazosin. Based on these results, a three-dimensional quantitative structure-activity relationship study was performed using a Self-Organizing Molecular Field Analysis method to provide insight for the future development of alpha(1)-adrenoceptor antagonists.
A Longitudinal Investigation of the Relationship between Teacher Preparation and Teacher Retention

ERIC Educational Resources Information Center

Zhang, Guili; Zeller, Nancy

2016-01-01

Few issues in education threaten the nation as seriously as the present and growing shortage of teachers. Teacher attrition is high among teachers across the nation and is one of the most serious causes of teacher shortage (Ingersoll, 2004). As policy makers rush to address this problem, research is needed to examine the retention effects of…
Actual Drawing of Histological Images Improves Knowledge Retention

ERIC Educational Resources Information Center

Balemans, Monique C. M.; Kooloos, Jan G. M.; Donders, A. Rogier T.; Van der Zee, Catharina E. E. M.

2016-01-01

Medical students have to process a large amount of information during the first years of their study, which has to be retained over long periods of nonuse. Therefore, it would be beneficial when knowledge is gained in a way that promotes long-term retention. Paper-and-pencil drawings for the uptake of form-function relationships of basic tissues…
Mechanisms of deterioration of nutrients. [retention of flavor during freeze drying

NASA Technical Reports Server (NTRS)

Karel, M.; Flink, J. M.

1975-01-01

The retention of flavor during freeze drying was studied with model systems. Mechanisms by which flavor retention phenomena is explained were developed and process conditions specified so that flavor retention is optimized. The literature is reviewed and results of studies of the flavor retention behavior of a number of real food products, including both liquid and solid foods are evaluated. Process parameters predicted by the mechanisms to be of greatest significance are freezing rate, initial solids content, and conditions which result in maintenance of sample structure. Flavor quality for the real food showed the same behavior relative to process conditions as predicted by the mechanisms based on model system studies.
The Baptist Health Nurse Retention Questionnaire: A Methodological Study, Part 1.

PubMed

Lengerich, Alexander; Bugajski, Andrew; Marchese, Matthew; Hall, Brittany; Yackzan, Susan; Davies, Claire; Brockopp, Dorothy

2017-05-01

The purposes of this study were to develop and test the Baptist Health Nurse Retention Questionnaire (BHNRQ) and examine the importance of nurse retention factors. Multiple factors, including increasing patient acuity levels, have led to concerns regarding nurse retention. An understanding of current factors related to retention is limited. To establish the psychometric properties of the BHNRQ, data were collected from 279 bedside nurses at a 391-bed, Magnet® redesignated community hospital. A principal component analysis was conducted to determine the subscale structure of the BHNRQ. Additional analyses were conducted related to content validity and test-retest reliability. The results of the principal components analysis revealed 3 subscales: nursing practice, management, and staffing. Analyses demonstrate that the BHNRQ is a reliable and valid instrument for measuring nurse retention factors. The BHNRQ was found to be a clinically useful instrument for measuring important factors related to nurse retention.
Green-tree retention in harvest units: Boon or bust for biodiversity?

Treesearch

Jonathan Thompson

2007-01-01

In response to societal concerns about clearcutting in the Pacific Northwest, structural or green-tree retention is now an integral part of harvest prescriptions on federal lands. However, the benefits of different levels or patterns of retention for the ecological, microclimatic, and aesthetic attributes of resulting forest stands remain speculative.
Improving Student Retention in Online College Classes: Qualitative Insights from Faculty

ERIC Educational Resources Information Center

Russo-Gleicher, Rosalie J.

2014-01-01

This article provides qualitative insights into addressing the issue of student retention in online classes in higher education. Semi-structured, in-depth interviews were conducted at random with 16 faculty who teach online courses at a large community college in the Northeast about how to improve online student retention. Qualitative analysis…
Tritium retention in reduced-activation ferritic/martensitic steels

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

Hatano, Y.; Abe, S.; Matsuyama, M.

Reduced-activation ferritic/martensitic (RAFM) steels are structural material candidates for breeding blankets of future fusion reactors. Therefore, tritium (T) retention in RAFM steels is an important problem in assessing the T inventory of blankets. In this study, specimens of RAFM steels were subjected to irradiation of 20 MeV W ions to 0.54 displacements per atom (dpa), exposure to high flux D plasmas at 400 and 600 K and that to pulsed heat loads. The specimens thus prepared were exposed to DT gas at 473 K. Despite severe modification in the surface morphology, heat loads had negligible effects on T retention. Significantmore » increase in T retention at the surface and/or subsurface was observed after D plasma exposure. However, T trapped at the surface/subsurface layer was easily removed by maintaining the specimens in the air at about 300 K. Displacement damage led to increase in T retention in the bulk due to the trapping effects of defects, and T trapped was stable at 300 K. It was therefore concluded that displacement damages had the largest influence on T retention under the present conditions.« less
A Structural Equation Model of Predictors of Online Learning Retention

ERIC Educational Resources Information Center

Lee, Youngju; Choi, Jaeho

2013-01-01

This study examined the effects of internal academic locus of control (ALOC), learning strategies, flow experience, and student satisfaction on student retention in online learning courses. A total number of 282 adult students at the Korea National Open University participated in the study by completing an online survey adopted from previous…

Design, synthesis, antiviral activity and three-dimensional quantitative structure-activity relationship study of novel 1,4-pentadien-3-one derivatives containing the 1,3,4-oxadiazole moiety.

PubMed

Gan, Xiuhai; Hu, Deyu; Li, Pei; Wu, Jian; Chen, Xuewen; Xue, Wei; Song, Baoan

2016-03-01

1,4-Pentadien-3-one and 1,3,4-oxadiazole derivatives possess good antiviral activities, and their substructure units are usually used in antiviral agent design. In order to discover novel molecules with high antiviral activities, a series of 1,4-pentadien-3-one derivatives containing the 1,3,4-oxadiazole moiety were designed and synthesised. Bioassays showed that most of the title compounds exhibited good inhibitory activities against tobacco mosaic virus (TMV) in vivo. The compound 8f possessing the best protective activity against TMV had an EC50 value of 135.56 mg L(-1) , which was superior to that of ribavirin (435.99 mg L(-1) ). Comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA) techniques were used in three-dimensional quantitative structure-activity relationship (3D-QSAR) studies of protective activities, with values of q(2) and r(2) for the CoMFA and CoMSIA models of 0.751 and 0.775 and 0.936 and 0.925 respectively. Compound 8k with higher protective activity (EC50 = 123.53 mg L(-1) ) according to bioassay was designed and synthesised on the basis of the 3D-QSAR models. Some of the title compounds displayed good antiviral activities. 3D-QSAR models revealed that the appropriate compact electron-withdrawing and hydrophobic group at the benzene ring could enhance antiviral activity. These results could provide important structural insights for the design of highly active 1,4-pentadien-3-one derivatives. © 2015 Society of Chemical Industry.
Providing grief resolution as an oncology nurse retention strategy: a literature review.

PubMed

Hildebrandt, Lori

2012-12-01

Oncology nurses play a pivotal role in optimizing care provided to patients at the end of life (EOL). Although oncology nurses commonly provide EOL care and witness deaths of patients that they have maintained long-standing relationships with, they are frequently excluded from grief resolution endeavors. With a worldwide shortage of oncology nurses, retention is paramount to ensuring that the care patients with cancer receive is not jeopardized. Various strategies were identified to resolve grief and increase nurse retention, including creating supportive work environments, debriefing with colleagues, providing EOL and grief education, and altering patient care assignments. Future research on emerging technologies and their effects on oncology nurse coping and retention strategies also was suggested.
Understanding the Molecular Determinant of Reversible Human Monoamine Oxidase B Inhibitors Containing 2H-Chromen-2-One Core: Structure-Based and Ligand-Based Derived Three-Dimensional Quantitative Structure-Activity Relationships Predictive Models.

PubMed

Mladenović, Milan; Patsilinakos, Alexandros; Pirolli, Adele; Sabatino, Manuela; Ragno, Rino

2017-04-24

Monoamine oxidase B (MAO B) catalyzes the oxidative deamination of aryalkylamines neurotransmitters with concomitant reduction of oxygen to hydrogen peroxide. Consequently, the enzyme's malfunction can induce oxidative damage to mitochondrial DNA and mediates development of Parkinson's disease. Thus, MAO B emerges as a promising target for developing pharmaceuticals potentially useful to treat this vicious neurodegenerative condition. Aiming to contribute to the development of drugs with the reversible mechanism of MAO B inhibition only, herein, an extended in silico-in vitro procedure for the selection of novel MAO B inhibitors is demonstrated, including the following: (1) definition of optimized and validated structure-based three-dimensional (3-D) quantitative structure-activity relationships (QSAR) models derived from available cocrystallized inhibitor-MAO B complexes; (2) elaboration of SAR features for either irreversible or reversible MAO B inhibitors to characterize and improve coumarin-based inhibitor activity (Protein Data Bank ID: 2V61 ) as the most potent reversible lead compound; (3) definition of structure-based (SB) and ligand-based (LB) alignment rule assessments by which virtually any untested potential MAO B inhibitor might be evaluated; (4) predictive ability validation of the best 3-D QSAR model through SB/LB modeling of four coumarin-based external test sets (267 compounds); (5) design and SB/LB alignment of novel coumarin-based scaffolds experimentally validated through synthesis and biological evaluation in vitro. Due to the wide range of molecular diversity within the 3-D QSAR training set and derived features, the selected N probe-derived 3-D QSAR model proves to be a valuable tool for virtual screening (VS) of novel MAO B inhibitors and a platform for design, synthesis and evaluation of novel active structures. Accordingly, six highly active and selective MAO B inhibitors (picomolar to low nanomolar range of activity) were disclosed as a
QSAR, QSPR and QSRR in Terms of 3-D-MoRSE Descriptors for In Silico Screening of Clofibric Acid Analogues.

PubMed

Di Tullio, Maurizio; Maccallini, Cristina; Ammazzalorso, Alessandra; Giampietro, Letizia; Amoroso, Rosa; De Filippis, Barbara; Fantacuzzi, Marialuigia; Wiczling, Paweł; Kaliszan, Roman

2012-07-01

A series of 27 analogues of clofibric acid, mostly heteroarylalkanoic derivatives, have been analyzed by a novel high-throughput reversed-phase HPLC method employing combined gradient of eluent's pH and organic modifier content. The such determined hydrophobicity (lipophilicity) parameters, log kw , and acidity constants, pKa , were subjected to multiple regression analysis to get a QSRR (Quantitative StructureRetention Relationships) and a QSPR (Quantitative Structure-Property Relationships) equation, respectively, describing these pharmacokinetics-determining physicochemical parameters in terms of the calculation chemistry derived structural descriptors. The previously determined in vitro log EC50 values - transactivation activity towards PPARα (human Peroxisome Proliferator-Activated Receptor α) - have also been described in a QSAR (Quantitative StructureActivity Relationships) equation in terms of the 3-D-MoRSE descriptors (3D-Molecule Representation of Structures based on Electron diffraction descriptors). The QSAR model derived can serve for an a priori prediction of bioactivity in vitro of any designed analogue, whereas the QSRR and the QSPR models can be used to evaluate lipophilicity and acidity, respectively, of the compounds, and hence to rational guide selection of structures of proper pharmacokinetics. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Fuel nozzle tube retention

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

Cihlar, David William; Melton, Patrick Benedict

A system for retaining a fuel nozzle premix tube includes a retention plate and a premix tube which extends downstream from an outlet of a premix passage defined along an aft side of a fuel plenum body. The premix tube includes an inlet end and a spring support feature which is disposed proximate to the inlet end. The premix tube extends through the retention plate. The spring retention feature is disposed between an aft side of the fuel plenum and the retention plate. The system further includes a spring which extends between the spring retention feature and the retention plate.
The Effect of Grouping and Presenting Collocations on Retention

ERIC Educational Resources Information Center

Akpinar, Kadriye Dilek; Bardakçi, Mehmet

2015-01-01

The aim of this study is two-fold. Firstly, it attempts to determine the role of presenting collocations by organizing them based on (i) the keyword, (ii) topic related and (iii) grammatical aspect on retention of collocations. Secondly, it investigates the relationship between participants' general English proficiency and the presentation types…
Career Goals and Retention-Related Factors among College Freshmen

ERIC Educational Resources Information Center

Hull-Blanks, Elva; Robinson Kurpius, Sharon E.; Befort, Christie; Sollenberger, Sonja; Nicpon, Megan Foley; Huser, Laura

2005-01-01

The relationships of four types of career goals (job related, school related, value related, and unknown) with factors of school retention, academic performance, self-esteem, educational self-efficacy, and school and career commitment are studied among 401 first-semester college freshmen. Differences in types of goals based on gender are also…
Influence of biochar on the physical, chemical and retention properties of an amended sandy soil

NASA Astrophysics Data System (ADS)

Baiamonte, Giorgio; De Pasquale, Claudio; Parrino, Francesco; Crescimanno, Giuseppina

2017-04-01

Soil porosity plays an important role in soil-water retention and water availability to crops, potentially affecting both agricultural practices and environmental sustainability. The pore structure controls fluid flow and transport through the soil, as well as the relationship between the properties of individual minerals and plants. Moreover, the anthropogenic pressure on soil properties has produced numerous sites with extensive desertification process close to residential areas. Biochar (biologically derived charcoal) is produced by pyrolysis of biomasses under low oxygen conditions, and it can be applied for recycling organic waste in soils and increase soil fertility, improving soil structure and enhancing soil water storage and soil water movement. Soil application of biochar might have agricultural, environmental and sustainability advantages over the use of organic manures or compost, as it is a porous material with a high inner surface area. The main objectives of the present study were to investigate the possible application of biochar from forest residues, derived from mechanically chipped trunks and large branches of Abies alba M., Larix decidua Mill., Picea excelsa L., Pinus nigra A. and Pinus sylvestris L. pyrolysed at 450 °C for 48h, to improve soil structural and hydraulic properties (achieving a stabilization of soil). Different amount of biochar were added to a desertic sandy soil, and the effect on soil porosity water retention and water available to crops were investigated. The High Energy Moisture Characteristic (HEMC) technique was applied to investigate soil-water retention at high-pressure head levels. The adsorption and desorption isotherms of N2 on external surfaces were also determined in order to investigate micro and macro porosity ratio. Both the described model of studies on adsorption-desorption experiments with the applied isotherms model explain the increasing substrate porosity with a particular attention to the macro and micro
Synthesis, fungicidal activity, structure-activity relationships (SARs) and density functional theory (DFT) studies of novel strobilurin analogues containing arylpyrazole rings.

PubMed

Liu, Yuanyuan; Lv, Kunzhi; Li, Yi; Nan, Qiuli; Xu, Jinyuan

2018-05-18

A series of novel strobilurin analogues (1a-1f, 2a-2e, 3a-3e) containing arylpyrazole rings were synthesized and characterized by NMR spectroscopy. The structures of 1f, 2b and 3b were also determined by single crystal X-ray diffraction analysis. These analogues were collected together with other twenty-eight similar compounds 4a-4f, 5a-5h, 6a-6h and 7a-7f from our previous studies, for in vitro bioassays and thorough structure-activity relationships (SARs) studies. Most compounds exhibited excellent-to-good fungicidal activity against Rhizoctonia solani, especially 5c, 7a, 6c, and 3b with 98.94%, 83.40%, 71.40% and 65.87% inhibition rates at 0.1 μg mL -1 , respectively, better than commercial pyraclostrobin. Comparative molecular field analysis (CoMFA) was employed to study three-dimensional quantitative structure-activity relationships (3D-QSARs). Density functional theory (DFT) calculation was also carried out to provide more information regarding SARs. The present work provided some hints for developing novel strobilurin fungicides.
The Relationship between Shyness and Internet Addiction: A Quantitative Study on Middle and Post Secondary School Students

ERIC Educational Resources Information Center

Hollingsworth, W. Craig

2005-01-01

This small scale quantitative study looks into the relationship between shyness and internet addiction in middle school students. This study has been conducted on the belief that shyness is a possible predictor of Internet Addiction. To prove this hypothesis a questionnaire was created and distributed to 53 middle school students and 159 post…
Racial Privilege in the Professoriate: An Exploration of Campus Climate, Retention, and Satisfaction

ERIC Educational Resources Information Center

Jayakumar, Uma M.; Howard, Tyrone C.; Allen, Walter R.; Han, June C.

2009-01-01

This study applies the principles of critical race theory to examine quantitatively the experiences of a national sample of 37,582 faculty. Among the key factors influencing retention and satisfaction are campus racial climate, autonomy and independence, and the review and promotion process. Results support the value of examining faculty of color…
Quantitative structure-activity relationships for primary aerobic biodegradation of organic chemicals in pristine surface waters: starting points for predicting biodegradation under acclimatization.

PubMed

Nolte, Tom M; Pinto-Gil, Kevin; Hendriks, A Jan; Ragas, Ad M J; Pastor, Manuel

2018-01-24

Microbial biomass and acclimation can affect the removal of organic chemicals in natural surface waters. In order to account for these effects and develop more robust models for biodegradation, we have compiled and curated removal data for un-acclimated (pristine) surface waters on which we developed quantitative structure-activity relationships (QSARs). Global analysis of the very heterogeneous dataset including neutral, anionic, cationic and zwitterionic chemicals (N = 233) using a random forest algorithm showed that useful predictions were possible (Q ext 2 = 0.4-0.5) though relatively large standard errors were associated (SDEP ∼0.7). Classification of the chemicals based on speciation state and metabolic pathway showed that biodegradation is influenced by the two, and that the dependence of biodegradation on chemical characteristics is non-linear. Class-specific QSAR analysis indicated that shape and charge distribution determine the biodegradation of neutral chemicals (R 2 ∼ 0.6), e.g. through membrane permeation or binding to P450 enzymes, whereas the average biodegradation of charged chemicals is 1 to 2 orders of magnitude lower, for which degradation depends more directly on cellular uptake (R 2 ∼ 0.6). Further analysis showed that specific chemical classes such as peptides and organic halogens are relatively less biodegradable in pristine surface waters, resulting in the need for the microbial consortia to acclimate. Additional literature data was used to verify an acclimation model (based on Monod-type kinetics) capable of extrapolating QSAR predictions to acclimating conditions such as in water treatment, downstream lakes and large rivers under μg L -1 to mg L -1 concentrations. The framework developed, despite being based on multiple assumptions, is promising and needs further validation using experimentation with more standardised and homogenised conditions as well as adequate characterization of the inoculum used.
Retention properties of novel beta-CD bonded stationary phases in reversed-phase HPLC mode.

PubMed

Zhao, Yanyan; Guo, Zhimou; Zhang, Yongping; Xue, Xingya; Xu, Qing; Li, Xiuling; Liang, Xinmiao; Zhang, Yukui

2009-05-15

With the given special structures, the CD bonded stationary phases are expected to have complementary retention properties with conventional C18 stationary phase, which will be helpful to enhance the polar selectivity in RP mode separation. In this work, two beta-cyclodextrin (beta-CD) bonded stationary phases for reversed-phase HPLC, including 1, 12-dodecyldiol linked beta-CD stationary phase (CD1) and olio (ethylene glycol) (OEG) linked beta-CD stationary phase (CD2), have been synthesized via click chemistry. The resulting materials were characterized with FT-IR and elemental analysis, which proved the successful immobilization of ligands. The similarities and differences in retention characteristics between the CD and C18 stationary phases have been elucidated by using comparative linear solvation energy relationships (LSERs). The force related to solute McGowan volume has no significant difference, while the hydrogen bonding and dipolar interactions between solutes and CD stationary phases are stronger than between solutes and C18, which is attributed to the special structures (CD and triazole groups) of CD stationary phases. Chemical origins are interpreted by comparison between CD1 and CD2. Similar dispersive interactions of CD1 and CD2 are attributed to their similar length of spacer arms. CD2 which contains OEG spacer arm has relative weaker HBD acidity but stronger HBA basicity. CD stationary phases display no serious different methylene selectivity and higher polar selectivity than in the case of C18. Higher acid selectivity and lower basic selectivity are observed on CD2 than on CD1. Distinctive retention properties and good complementary separation selectivity to C18 make the novel CD bonded stationary phases available for more application in RPLC.
QSRR using evolved artificial neural network for 52 common pharmaceuticals and drugs of abuse in hair from UPLC-TOF-MS.

PubMed

Noorizadeh, Hadi; Farmany, Abbas; Narimani, Hojat; Noorizadeh, Mehrab

2013-05-01

A quantitative structure-retention relationship (QSRR) study based on an artificial neural network (ANN) was carried out for the prediction of the ultra-performance liquid chromatography-Time-of-Flight mass spectrometry (UPLC-TOF-MS) retention time (RT) of a set of 52 pharmaceuticals and drugs of abuse in hair. The genetic algorithm was used as a variable selection tool. A partial least squares (PLS) method was used to select the best descriptors which were used as input neurons in neural network model. For choosing the best predictive model from among comparable models, square correlation coefficient R(2) for the whole set calculated based on leave-group-out predicted values of the training set and model-derived predicted values for the test set compounds is suggested to be a good criterion. Finally, to improve the results, structure-retention relationships were followed by a non-linear approach using artificial neural networks and consequently better results were obtained. This also demonstrates the advantages of ANN. Copyright © 2011 John Wiley & Sons, Ltd.
Recruitment and Retention of Low-SES Ethnic Minority Couples in Intervention Research at the Transition to Parenthood.

PubMed

Baucom, Katherine J W; Chen, Xiao S; Perry, Nicholas S; Revolorio, Kaddy Y; Reina, Astrid; Christensen, Andrew

2017-03-22

Low-SES couples have limited resources to manage the chronic and acute stressors with which they are disproportionately faced. Although these couples are at greater risk for negative individual and relationship outcomes, evaluations of the impact of couple relationship education (CRE) in low-SES couples have been plagued by methodological problems, most notably challenges associated with recruitment and retention. We review the literature on challenges couples face associated with low-SES, as well as on recruitment, retention, and CRE in low-SES, ethnic minority populations. We illustrate some of these challenges in a case study of CRE for low-SES couples transitioning to parenthood. In this pilot study, 21 couples were recruited from a community health clinic and randomized to either an experimental treatment condition (EXP; N = 11) or a treatment-as-usual control condition (TAU; N = 10). This study sought to mitigate documented challenges with recruitment and retention: We leveraged community partnerships, attempted to build and maintain strong relationships with study participants, provided incentives for assessments as well as intervention meetings, and attempted to reduce potential barriers to enrollment and retention. Nonetheless, we had low rates of recruitment and retention. We integrate these findings and experiences with our review of previous work in this area. We make recommendations for future CRE research and practice that have potential implications for public policy in this area. © 2017 Family Process Institute.
Learner Retention of Medical Vocabulary Based on Instructional Format and Success in Medical Coding

ERIC Educational Resources Information Center

Gruich, Madelon Reed

2013-01-01

This quantitative research study explores the correlation between instructional formats and the measurement of knowledge retention, as well as subsequent course mastery and whether other factors such as age, ethnicity, gender, number of study hours, number of work hours, and family responsibilities influence learning outcomes. The healthcare data…
Structure-function relationships in tendons: a review

PubMed Central

Benjamin, M; Kaiser, E; Milz, S

2008-01-01

The purpose of the current review is to highlight the structure-function relationship of tendons and related structures to provide an overview for readers whose interest in tendons needs to be underpinned by anatomy. Because of the availability of several recent reviews on tendon development and entheses, the focus of the current work is primarily directed towards what can best be described as the ‘tendon proper’ or the ‘mid-substance’ of tendons. The review covers all levels of tendon structure from the molecular to the gross and deals both with the extracellular matrix and with tendon cells. The latter are often called ‘tenocytes’ and are increasingly recognized as a defined cell population that is functionally and phenotypically distinct from other fibroblast-like cells. This is illustrated by their response to different types of mechanical stress. However, it is not only tendon cells, but tendons as a whole that exhibit distinct structure-function relationships geared to the changing mechanical stresses to which they are subject. This aspect of tendon biology is considered in some detail. Attention is briefly directed to the blood and nerve supply of tendons, for this is an important issue that relates to the intrinsic healing capacity of tendons. Structures closely related to tendons (joint capsules, tendon sheaths, pulleys, retinacula, fat pads and bursae) are also covered and the concept of a ‘supertendon’ is introduced to describe a collection of tendons in which the function of the whole complex exceeds that of its individual members. Finally, attention is drawn to the important relationship between tendons and fascia, highlighted by Wood Jones in his concept of an ‘ectoskeleton’ over half a century ago – work that is often forgotten today. PMID:18304204
Alcohol Consumption and Academic Retention in First-Year College Students

ERIC Educational Resources Information Center

Liguori, Gary; Lonbaken, Barb

2015-01-01

Objectives: This study attempted to identify relationships between alcohol consumption and first-to-second-year student retention among college students. Methods: 820 students in general education courses completed an online wellness assessment at four separate time points, including questions related to alcohol consumption. Data were analyzed…
Identification of mutagenic transformation products generated during oxidation of 3-methyl-4-nitrophenol solutions by orbitrap tandem mass spectrometry and quantitative structure-activity relationship analyses.

PubMed

Matsushita, Taku; Honda, Shiho; Kuriyama, Taisuke; Fujita, Yuki; Kondo, Takashi; Matsui, Yoshihiko; Shirasaki, Nobutaka; Takanashi, Hirokazu; Kameya, Takashi

2018-02-01

We used Ames assays to investigate the effects of ozonation (designated O 3 ), ozonation followed by chlorination (O 3 /Cl), an advanced oxidation process (AOP, UV/H 2 O 2 ), and AOP followed by chlorination (AOP/Cl) on the mutagenicity of solutions of 3-methyl-4-nitrophenol (3M4NP), a major environmental degradation product of the organophosphorus insecticide fenitrothion. Whereas O 3 did not induce mutagenicity, O 3 /Cl, AOP, and AOP/Cl converted 3M4NP into mutagenic transformation products (TPs). Using liquid chromatography-mass spectrometry, we detected a total of 138 peaks in the solutions subjected to O 3 /Cl, AOP, and AOP/Cl. To elucidate the TPs responsible for the observed mutagenicity, we performed simple regression analyses of the relationship between the area of each peak and the observed mutagenicity of samples withdrawn periodically during each oxidation process. The area of each of 10 peaks was found to be positively correlated (r 2 ≥ 0.8) with the observed mutagenicity, suggesting that the TPs corresponding to these peaks contributed to the mutagenicity. After taking into account the consistency of mutagenicity induction by the oxidation processes and analyzing the peaks by tandem mass spectrometry, we identified 3 TPs, corresponding to 6 peaks, as candidate mutagens. These TPs were assessed by means of 4 quantitative structure-activity relationship (QSAR) models, and all 3 were predicted to be mutagenic by at least one model. This result was consistent with our assumption that these TPs were mutagens. Ames assays of an authentic sample of one of the 3 TPs revealed that it did not contribute to the mutagenicity. This left 3-methoxy-4-nitrophenol and 2-[(E)-[(2,5-dihydroxyphenyl) methylidene]amino]-5-dihydroxybenzaldehyde on the list of mutagens suspected of contributing to the mutagenicity induced by AOP. No TPs were identified as candidate mutagens responsible for the mutagenicity induced by O 3 /Cl and AOP/Cl. Copyright © 2017 Elsevier Ltd
Gender, Math Confidence, and Grit: Relationships with Quantitative Skills and Performance in an Undergraduate Biology Course

PubMed Central

Flanagan, K. M.; Einarson, J.

2017-01-01

In a world filled with big data, mathematical models, and statistics, the development of strong quantitative skills is becoming increasingly critical for modern biologists. Teachers in this field must understand how students acquire quantitative skills and explore barriers experienced by students when developing these skills. In this study, we examine the interrelationships among gender, grit, and math confidence for student performance on a pre–post quantitative skills assessment and overall performance in an undergraduate biology course. Here, we show that females significantly underperformed relative to males on a quantitative skills assessment at the start of term. However, females showed significantly higher gains over the semester, such that the gender gap in performance was nearly eliminated by the end of the semester. Math confidence plays an important role in the performance on both the pre and post quantitative skills assessments and overall performance in the course. The effect of grit on student performance, however, is mediated by a student’s math confidence; as math confidence increases, the positive effect of grit decreases. Consequently, the positive impact of a student’s grittiness is observed most strongly for those students with low math confidence. We also found grit to be positively associated with the midterm score and the final grade in the course. Given the relationships established in this study among gender, grit, and math confidence, we provide “instructor actions” from the literature that can be applied in the classroom to promote the development of quantitative skills in light of our findings. PMID:28798209

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